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   "cell_type": "code",
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    "\"\"\"***python调用包的引用部分***\"\"\"\n",
    "# 科学计算基础库，用于存储和处理大型矩阵\n",
    "import numpy as np\n",
    "# 基于 NumPy 的数据操作库，提供了高效地操作大型数据集所需的工具和方法\n",
    "import pandas as pd\n",
    "# 绘图库，支持多种可视化功能\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "# 基于Pandas和Matplotlib的地理数据处理、绘图库，以及GeoPandas的依赖项\n",
    "import geopandas as gpd\n",
    "# 用于查找符合特定规则的文件路径名\n",
    "import glob\n",
    "# 处理日期和时间的标准库\n",
    "import time, datetime\n",
    "# 生成随机数的模块\n",
    "import random as rd\n",
    "# 数学库\n",
    "import math\n",
    "from math import tan, atan, acos, sin, cos, asin, sqrt, radians\n",
    "# 平面特征进行集合理论分析和操作,几何对象的基本类型是点、曲线和曲面\n",
    "from shapely.geometry import LineString, Point\n",
    "from shapely.ops import nearest_points\n",
    "# 经纬坐标模块\n",
    "import pyproj\n",
    "from pyproj import Transformer\n",
    "# 基于Python语言的机器学习工具\n",
    "from sklearn import metrics\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.cluster import DBSCAN\n",
    "from scipy.spatial.distance import pdist, squareform, euclidean\n",
    "# 用于创建、操作和研究复杂网络的结构、动态和功能\n",
    "import networkx as nx\n",
    "from networkx.algorithms import community\n",
    "# HTTP库\n",
    "import requests\n",
    "from tqdm import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-12T09:05:00.628262Z",
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   "source": [
    "def get_sub_trajectory(df):\n",
    "    '''\n",
    "    输入：\n",
    "    df: 轨迹DataFrame。\n",
    "\n",
    "    输出：\n",
    "    loads,no_loads,ODs: 载客轨迹、空驶轨迹、上车点与下车点，实习用到后面两个。\n",
    "    '''\n",
    "    loads = []\n",
    "    no_loads = []\n",
    "    ODs = []\n",
    "\n",
    "    # 记录每一段轨迹的开始\n",
    "    idx1 = -1\n",
    "    # 记录每一段轨迹的结束\n",
    "    idx2 = -1\n",
    "    # 记录原始的出租车状态：空车/重车\n",
    "    old_status = ''\n",
    "\n",
    "    for index, row in tqdm(df.iterrows()):\n",
    "        status = row['空车/重车']\n",
    "        # 初始化，当对索引号为0的时\n",
    "        if index == 0:\n",
    "            idx1 = index\n",
    "            old_status = status\n",
    "\n",
    "        # 判断状态是否转变，当发生了改变（status != old_status）时\n",
    "        if status != old_status:\n",
    "            # 将两次分界点之间的状态作为一段轨迹，取df的子集df[轨迹开始index1:轨迹结束idx2 + 1]\n",
    "            sub_df = df[idx1:idx2 + 1]\n",
    "            sub_list = sub_df.values.tolist()\n",
    "            # 当状态为'重车'时，说明此时出租车是载客的状态，记录在loads轨迹集中\n",
    "            if old_status == '重车':\n",
    "                loads.append(sub_df)\n",
    "                # sub_list[-1]表示这一段轨迹的最后一个数据点\n",
    "                temp_d = sub_list[-1]\n",
    "                # 将这个数据点记录为“下车点”，并添加到ODs中\n",
    "                temp_d.append('下车点')\n",
    "                ODs.append(temp_d)\n",
    "            else:\n",
    "                # 当状态不为‘重车’，即为‘空车’时，说明此时出租车是空车的状态，记录在no_loads数据集中\n",
    "                no_loads.append(sub_df)\n",
    "                # sub_list[0]表示这一段轨迹的第一个数据点\n",
    "                temp_p = sub_list[0]\n",
    "                # 将这个数据点记录为“上车点”，并添加到ODs中\n",
    "                temp_p.append('上车点')\n",
    "                ODs.append(temp_p)\n",
    "            # 当前时刻即为下一个时段的开始\n",
    "            idx1 = index\n",
    "            idx2 = index\n",
    "            # 状态更新为下一个时段的状态\n",
    "            old_status = status\n",
    "        else:\n",
    "            # 当状态没有发生改变时，轨迹结束index往后推一个\n",
    "            idx2 = index\n",
    "\n",
    "    # 由于最后一个时段没有转折点了，因此对最后一个时段的数据进行处理并归档\n",
    "    sub_df = df[idx1:idx2 + 1]\n",
    "    if old_status == '重车':\n",
    "        loads.append(sub_df)\n",
    "    else:\n",
    "        no_loads.append(sub_df)\n",
    "    return loads, no_loads, ODs\n",
    "\n",
    "\n",
    "# 获取能够满足一天中一辆车的第一个OD点是上车点，最后一个OD点是下车点的数据区间\n",
    "def find_indexes(od_list):\n",
    "    daybegin = 0\n",
    "    dayend = -1\n",
    "    # 遍历整个od_list\n",
    "    for i in range(0, len(od_list)):\n",
    "        # 我们希望每一辆出租车的第一个上下车点为上车点，当点的属性为下车点时，继续\n",
    "        if od_list[i][-1] == '下车点':\n",
    "            pass\n",
    "        else:\n",
    "            # 如果点的属性不是下车点，则为上车点，这时将点号记录为daybegin，等待输出\n",
    "            daybegin = i\n",
    "            break\n",
    "    for i in range(1, len(od_list)):\n",
    "        # 同上，这里我们希望每一辆出租车的最后一个上下车点为下车点，当点的属性为上车点时，继续\n",
    "        if od_list[len(od_list) - i][-1] == '上车点':\n",
    "            pass\n",
    "        else:\n",
    "            # 如果点的属性不是下车点，则为上车点，这时将（点号+1）记录为dayend，目的是为了方便直接获取截取的子集段，等待输出\n",
    "            dayend = len(od_list) - i + 1\n",
    "            break\n",
    "    return daybegin, dayend\n",
    "\n",
    "\n",
    "# 去掉每辆车里“落单”的上车点、下车点\n",
    "def align_ODs(od_list_sub):\n",
    "    # 数据过少，直接抛弃掉这个出租车的数据\n",
    "    if len(od_list_sub) < 2:\n",
    "        return []\n",
    "    else:\n",
    "        # cur表示这辆出租车的第一个数据点的“上下车点”属性\n",
    "        cur = od_list_sub[0][-1]\n",
    "        # num表示需要去除下来的上下车数据点的index\n",
    "        drop_nums = []\n",
    "        # 从第二个数据开始，遍历整个某辆出租车的上下车点子集\n",
    "        for i in range(1, len(od_list_sub)):\n",
    "            # 如果和前一个数据点的“上下车点”属性相同\n",
    "            if od_list_sub[i][-1] == cur:\n",
    "                # 如果同为上车点的话，保留最晚的一个上车点，把较早的几个上车点index加入num\n",
    "                if cur == '上车点':\n",
    "                    drop_nums.append((i - 1))\n",
    "                # 如果同为下车点的话，保留最早的一个下车点，把较晚的几个下车点index加入num\n",
    "                if cur == '下车点':\n",
    "                    drop_nums.append(i)\n",
    "            # 把当前数据点的“上下车点”属性记为cur，进入下一次循环\n",
    "            cur = od_list_sub[i][-1]\n",
    "        reserves = []\n",
    "        for i in range(0, len(od_list_sub)):\n",
    "            # 需要保留下来的上下车数据点，即index不在nums中\n",
    "            if i not in drop_nums: reserves.append(od_list_sub[i])\n",
    "        return reserves\n",
    "\n",
    "\n",
    "# 清洗+对齐出租车的OD点\n",
    "def filter_ODs(od_list):\n",
    "    # 返回值car_sorted_ODs为经过清洗和对齐之后每一辆出租车的上下车点的字典\n",
    "    # 返回值ODs_list为经过清洗和对齐之后所有出租车上下车点的列表\n",
    "    # od_list的各字段名为：出租车ID,定位时间,经度,纬度,方向,速度,空车/重车\n",
    "    # 利用循环遍历得到出租车的ID编号集合\n",
    "    num_list = list(set([ol[0] for ol in od_list]))\n",
    "    # 构建一个字典car_sorted_ODs，键即为出租车的ID，值暂时置为空\n",
    "    car_sorted_ODs = {n: [] for n in num_list}\n",
    "\n",
    "    # 以车辆为单位进行清洗，遍历上下车点列表，根据出租车ID将上下车点对应到每一个出租车ID上\n",
    "    for ol in od_list: car_sorted_ODs[ol[0]].append(ol)\n",
    "    # 确保一天中一辆车的第一个OD点是上车点，最后一个OD点是下车点\n",
    "    for key in tqdm(car_sorted_ODs):\n",
    "        # 对每一辆车进行数据清洗，确保一天中一辆车的第一个OD点是上车点，最后一个OD点是下车点\n",
    "        i_begin, i_end = find_indexes(car_sorted_ODs[key])\n",
    "        # 根据上面获得的一天的起止点截取子集\n",
    "        car_sorted_ODs[key] = car_sorted_ODs[key][i_begin:i_end]\n",
    "\n",
    "    # 对齐序列中的“上车点”和“下车点”，去掉每辆车里“落单”的上车点、下车点\n",
    "    for key in tqdm(car_sorted_ODs):\n",
    "        car_sorted_ODs[key] = align_ODs(car_sorted_ODs[key])\n",
    "\n",
    "    ODs_list = []\n",
    "    # 将所有出租车上下车点合在一起生成列表\n",
    "    for key in tqdm(car_sorted_ODs):\n",
    "        for od in car_sorted_ODs[key]: ODs_list.append(od)\n",
    "    return car_sorted_ODs, ODs_list\n",
    "\n",
    "\n",
    "# haversine计算方法\n",
    "def haversine(lonlat1, lonlat2):\n",
    "    lat1, lon1 = lonlat1\n",
    "    lat2, lon2 = lonlat2\n",
    "    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])\n",
    "    dlon = lon2 - lon1\n",
    "    dlat = lat2 - lat1\n",
    "    a = sin(dlat / 2) ** 2 + cos(lat1) * cos(lat2) * sin(dlon / 2) ** 2\n",
    "    c = 2 * asin(sqrt(a))\n",
    "    r = 6371  # Radius of earth in kilometers. Use 3956 for miles\n",
    "    return c * r * 1000\n",
    "\n",
    "\n",
    "# 过滤存在噪声点的OD点对\n",
    "def drop_noise(OD_df):\n",
    "    drop_indexes = []\n",
    "    i = 0\n",
    "    # 循环遍历整个OD_df列表\n",
    "    while i < len(OD_df) - 1:\n",
    "        # 当前上下车点对中只要有一个的热点类别为噪声点(-1)，将这两个点一起丢弃\n",
    "        if OD_df.loc[i].tolist()[-1] == -1 or OD_df.loc[i + 1].tolist()[-1] == -1:\n",
    "            drop_indexes.append(i)\n",
    "            drop_indexes.append(i + 1)\n",
    "        # 这里使循环控制变量直接+2，目的是为了每次可以取一对上下车点进行分析，如果其中一个出问题就丢掉这个上下车点对\n",
    "        i += 2\n",
    "    filter_df = OD_df.drop(index=drop_indexes)\n",
    "    return filter_df\n",
    "\n",
    "\n",
    "# 得到节点的列表\n",
    "def get_nodes(df):\n",
    "    '''\n",
    "    节点的属性列表包含了热点的ID、经度、纬度以及访问的频次\n",
    "    '''\n",
    "    # 聚类（热点）类别的所有唯一值的列表[0,1,...]\n",
    "    node_ids = list(set(df['热点类别'].tolist()))\n",
    "    # 生成一个列表nodes，nodes内部的每一个元素都是列表，且内嵌列表的第一个元素为热点类别，例如[[0],[1],...]\n",
    "    nodes = [[ids] for ids in node_ids]\n",
    "    # 统计每一个热点类别下包含的节点数\n",
    "    node_count = df['热点类别'].value_counts()\n",
    "    # 为列表nodes添加其他的补充属性\n",
    "    for node in nodes:\n",
    "        node.append({\n",
    "            # 聚类类别（即热点）的ID号\n",
    "            'Node_class_ID': node[0],\n",
    "            # 这个类别下的所有热点的经度均值\n",
    "            'AverLon': round(df[df['热点类别'] == node[0]]['经度'].mean(), 6),\n",
    "            # 这个类别下的所有热点的维度均值\n",
    "            'AverLat': round(df[df['热点类别'] == node[0]]['纬度'].mean(), 6),\n",
    "            # 这个类别下的热点数量\n",
    "            'counts': node_count[node[0]]})\n",
    "    # nodes的内容形如：[[0, {'Node_class_ID': 0, 'AverLon': 114.26951, 'AverLat': 30.614773, 'counts': 92}],[1,{}]...]\n",
    "    return nodes\n",
    "\n",
    "\n",
    "# 得到热点类别的唯一值列表\n",
    "def get_edges(df):\n",
    "    ids = list(set(df['热点类别'].tolist()))\n",
    "    # 边的矩阵，类似于邻接矩阵\n",
    "    edges = {}\n",
    "    # 初始化边矩阵\n",
    "    for i in range(0, len(ids)):\n",
    "        for j in range(i, len(ids)):\n",
    "            edges[(i, j)] = 0\n",
    "\n",
    "    n = 0\n",
    "    while n < len(df) - 1:\n",
    "        # 计算边矩阵的权重，每一个上下车点对之间的路径，对应对称矩阵的一次计数，来回都计数\n",
    "        e1 = (df.at[n, '热点类别'], df.at[n + 1, '热点类别'])\n",
    "        e2 = (df.at[n + 1, '热点类别'], df.at[n, '热点类别'])\n",
    "        if e1 in edges:\n",
    "            edges[e1] += 1\n",
    "        if e2 in edges:\n",
    "            edges[e2] += 1\n",
    "        # 取下一个上下车点对\n",
    "        n += 2\n",
    "\n",
    "    # NetworkX要求的带权边是“三元组”的形式，即(起点, 终点, 权重)\n",
    "    edge_list = []\n",
    "    for key in edges:\n",
    "        # NetworkX有的算法要求不能有self-loop（自循环），且权重需要大于0\n",
    "        if key[0] != key[1] and edges[key] > 0:\n",
    "            edge_list.append((key[0], key[1], edges[key]))\n",
    "    return edge_list\n",
    "\n",
    "\n",
    "# 绘制网络\n",
    "def paint_network(G, nodes):\n",
    "    # 叠加武汉市路网\n",
    "    wuhan_road = gpd.GeoDataFrame.from_file('../data/road/WuhanPartroad/WHroad.shp')\n",
    "    wuhan_road.plot(linewidth=0.5, alpha=0.5, color='grey')\n",
    "    pos_dict = {}\n",
    "    for node in nodes:\n",
    "        pos_dict[node[0]] = (node[1]['AverLon'], node[1]['AverLat'])  # 以点的经纬度作为绘制的坐标\n",
    "    nx.draw(G, node_size=30, pos=pos_dict, width=0.1)\n",
    "    plt.title(\"201811 出租车OD热点空间交互网络\")\n",
    "    # plt.show()\n",
    "\n",
    "\n",
    "# 以NetworkX实现封装的社区检测算法为基础，初步探索复杂网络中的社团结构发现与分析方法\n",
    "# 社区检测（community detection，又称社区发现、图聚类）即是用来揭示网络聚集行为的一种技术。\n",
    "# 社区检测实际就是一种网络聚类的方法，这里的“社区”在文献中并没有一种严格的定义，我们可以将其理解为一类具有相同特性的节点的集合。\n",
    "# 一般认为社团内部的点之间的连接相对稠密，而不同社团的点之间的连接相对稀疏。\n",
    "def gn_community_detect(g):\n",
    "    # greedy_modularity_communities 使用Clauset Newman-Moore贪婪的模块化最大化在图中查找社区\n",
    "    # 返回值为每个社区的节点(在这里是聚类/热点)集，每个社区一个\n",
    "    comp = community.greedy_modularity_communities(g, weight='weight')\n",
    "    # 对每一个社区的节点(在这里是聚类/热点)集排序后生成元组graph_community\n",
    "    graph_community = tuple(sorted(c) for c in comp)\n",
    "    node_community = {}\n",
    "    # 设置热点社区号的初始值为1，往后依次递增1\n",
    "    cid = 1\n",
    "    # 遍历每一个热点集\n",
    "    for c in graph_community:\n",
    "        # 遍历热点集中的每一个热点\n",
    "        for v in c:\n",
    "            # 逐个热点添加热点社区号\n",
    "            node_community[v] = cid\n",
    "        cid += 1\n",
    "    return graph_community, node_community\n",
    "\n",
    "\n",
    "# 通过百度地图API将经纬度转换成乡镇级的地理名称\n",
    "def coordinatesToPosition(lng, lat):\n",
    "    '''\n",
    "    函数输入为： lng: 经度, lat: 纬度\n",
    "\n",
    "    函数输出为：\n",
    "    address:     解析后的地理位置名称\n",
    "    province:    省份名称\n",
    "    city:        城市名\n",
    "    district:    县级行政区划名\n",
    "    town:        乡镇级行政区划\n",
    "    adcode:      县级行政区划编码\n",
    "    town_code:   镇级行政区划编码\n",
    "    business:    坐标所在商圈信息，如 \"人民大学,中关村,苏州街\"。最多返回3个\n",
    "    regionsName: 点所处的区域名\n",
    "    '''\n",
    "\n",
    "    AK = 'kbg5UcK25w0rYj6N7zsgJ3BzdxD0ODP4'\n",
    "    # coordtype=wgs84ll 表示输入的坐标为WGS84坐标\n",
    "    # extensions_town=true 表示行政区划返回乡镇级数据\n",
    "    url = 'http://api.map.baidu.com/reverse_geocoding/v3/?output=json&coordtype=wgs84ll&ak=%s&location=%s,%s&extensions_town=true&extensions_poi=1' % (\n",
    "        AK, lat, lng)\n",
    "    Result = requests.get(url)\n",
    "    # status_code为get请求的状态码，常用200表示成功接收请求并已完成整个处理过程\n",
    "    if Result.status_code == 200:\n",
    "        resultValue = Result.json()\n",
    "        # 'status'为服务状态码，返回为0表示服务请求正常召回\n",
    "        if resultValue['status'] == 0:\n",
    "            resultValue = resultValue['result']\n",
    "            resultValue = {\n",
    "                'address': resultValue['formatted_address'],\n",
    "                'province': resultValue['addressComponent']['province'],\n",
    "                'city': resultValue['addressComponent']['city'],\n",
    "                'district': resultValue['addressComponent']['district'],\n",
    "                'town': resultValue['addressComponent']['town'],\n",
    "                'adcode': resultValue['addressComponent']['adcode'],\n",
    "                'town_code': resultValue['addressComponent']['town_code'],\n",
    "                'business': resultValue['business'],\n",
    "                'regionsName': resultValue['sematic_description'],\n",
    "            }\n",
    "        else:\n",
    "            resultValue = None\n",
    "        return resultValue\n",
    "    else:\n",
    "        print('无法获取(%s,%s)的地理信息！' % (lat, lng))\n",
    "\n",
    "\n",
    "# 计算SSW和SSB\n",
    "# SSW计算方式为，首先计算1和每个类的类内轨迹距离最小值的差，然后取SSW为所有类的最大值\n",
    "# SSB计算方式为，首先计算不同类之间轨迹距离的最大值，然后用1与之相减\n",
    "# SSW越小则类内距离越小，SSB越大则类间距离越大\n",
    "def ssw_ssb(dtw_matr, cluster):\n",
    "    m = list(set(cluster))\n",
    "    ssw = 99999999.0\n",
    "    sswt = 0.0\n",
    "    ssb = 0.0\n",
    "    # 循环处理每一个聚类，计算聚类内的统计指标ssw\n",
    "    for i in m:\n",
    "        # idx1的含义为：聚类号为i的轨迹的序号\n",
    "        # 例如轨迹的聚类情况为[1 2 1 1 3 1]，idx1(i=1)=[0, 2, 3, 5]\n",
    "        idx1 = [c for c in range(len(cluster)) if cluster[c] == i]\n",
    "        # 如果这个聚类中只有一条轨迹时，指标sswt增加1\n",
    "        if len(idx1) == 1:\n",
    "            sswt += 1\n",
    "        # 这个聚类中不只有一条轨迹，这个时候需要计算每个类的类内轨迹距离最小值\n",
    "        else:\n",
    "            for p in idx1:\n",
    "                for q in idx1:\n",
    "                    # 计算这个聚类中的两条不同轨迹的轨迹距离的最小值，后面再用1减去ssw，再加上前面聚类中只有一条轨迹时的sswt，即(1-ssw+sswt)才是真正的ssw\n",
    "                    if p != q:\n",
    "                        if dtw_matr[p, q] < ssw:\n",
    "                            ssw = dtw_matr[p, q]\n",
    "        # 处理不同聚类之间的轨迹距离，计算聚类间的统计指标ssb\n",
    "        for j in m:\n",
    "            idx2 = [c for c in range(len(cluster)) if cluster[c] == j]\n",
    "            for p in idx1:\n",
    "                for q in idx2:\n",
    "                    # 计算不同类之间轨迹距离的最大值，后面再用1与之相减得到ssb，即(1-ssb)才为真正的ssb\n",
    "                    if dtw_matr[p, q] > ssb:\n",
    "                        ssb = dtw_matr[p, q]\n",
    "    # 这里指导代码的缩进有问题，导致了最后计算的ssw是负数，经过调整，往上减少一级缩进即可\n",
    "    return 1 - ssw + sswt, 1 - ssb\n",
    "\n",
    "\n",
    "# 计算WB值，WB值的计算公式为：M*SSW(M)/SSB(M)\n",
    "def WBindex(ssw, ssb, m):\n",
    "    m = float(m)\n",
    "    return m * ssw / ssb\n",
    "\n",
    "\n",
    "# DBSCAN聚类调参\n",
    "def DBSCAN_adjustParameters(distance_matrix, metric):\n",
    "    '''\n",
    "    Density-Based Spatial Clustering of Applications with Noise（具有噪声的基于密度的聚类方法）\n",
    "    是一种基于密度的空间聚类算法，将具有足够密度的区域划分为簇，并在具有噪声的空间数据库中发现任意形状的簇，它将簇定义为密度相连的点的最大集合。\n",
    "    传统的DBSCAN密度聚类算法，需要：邻域阈值(Eps)和点数阈值(min_samples)2个参数来对数据集进行聚类\n",
    "    fit_predict()从要素或距离矩阵执行DBSCAN聚类，并返回聚类标签\n",
    "\n",
    "    eps：DBSCAN算法参数，即我们的ϵ-邻域的距离阈值，和样本距离超过ϵ的样本点不在ϵ-邻域内。默认值是0.5，一般需要通过在多组值里面选择一个合适的阈值。\n",
    "    eps过大，则更多的点会落在核心对象的ϵ-邻域，此时我们的类别数可能会减少，本来不应该是一类的样本也会被划为一类。\n",
    "    反之则类别数可能会增大，本来是一类的样本却被划分开。\n",
    "\n",
    "    min_samples：DBSCAN算法参数，即样本点要成为核心对象所需要的ϵ-邻域的样本数阈值。默认值是5，一般需要通过在多组值里面选择一个合适的阈值。\n",
    "    通常和eps一起调参，在eps一定的情况下，min_samples过大，则核心对象会过少，此时簇内部分本来是一类的样本可能会被标为噪音点，类别数也会变多。\n",
    "    反之min_samples过小的话，则会产生大量的核心对象，可能会导致类别数过少。\n",
    "    '''\n",
    "    result = []\n",
    "    # 迭代次数，由于调参的过程耗时比较久，需要在中途给出适当的反馈\n",
    "    iterateTime = 0\n",
    "    # 迭代不同的eps值\n",
    "    for eps in tqdm(np.arange(175, 225, 1)):\n",
    "        # 迭代不同的min_samples值\n",
    "        for min_samples in range(5, 16):\n",
    "            DB_cluster_label = DBSCAN(eps=eps, min_samples=min_samples, metric='precomputed').fit_predict(\n",
    "                distance_matrix)\n",
    "            ssw, ssb = ssw_ssb(distance_matrix, DB_cluster_label.tolist())\n",
    "            # 统计各参数组合下的聚类个数（-1表示异常点）\n",
    "            n_clusters = len([i for i in set(DB_cluster_label) if i != -1])\n",
    "            WB = WBindex(ssw, ssb, n_clusters)\n",
    "            result.append({'eps': eps,\n",
    "                           'min_samples': min_samples,\n",
    "                           'n_clusters': n_clusters,\n",
    "                           'WBindex': WB,\n",
    "                           })\n",
    "            iterateTime += 1\n",
    "    # 将迭代后的结果存储到数据框中\n",
    "    result_df = pd.DataFrame(result)\n",
    "    WBindex_min = result_df.loc[:, \"WBindex\"].min()\n",
    "    best_result = result_df[result_df['WBindex'] == WBindex_min].reset_index(drop=True)\n",
    "    eps_best = best_result['eps'][0]\n",
    "    min_samples_best = best_result['min_samples'][0]\n",
    "    return result_df, eps_best, min_samples_best"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-12T08:58:26.818677Z",
     "start_time": "2023-05-12T08:58:03.428824Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "588407it [00:17, 34482.58it/s]\n",
      "100%|██████████| 1540/1540 [00:00<00:00, 1438580.88it/s]\n",
      "100%|██████████| 1540/1540 [00:00<00:00, 749591.29it/s]\n",
      "100%|██████████| 1540/1540 [00:00<?, ?it/s]\n"
     ]
    }
   ],
   "source": [
    "# 读取数据，这里直接读取经过轨迹数据预处理后得到的数据\n",
    "track_data = pd.read_csv('../data/processed/output_data/20181110_3_sorted.txt')\n",
    "# 提取出track_data中的上下车点ODs数据\n",
    "taxi_ODs = get_sub_trajectory(track_data)[2]\n",
    "\n",
    "# 清洗+对齐出租车的OD点\n",
    "filtered_ODs, filtered_ODs_list = filter_ODs(taxi_ODs)\n",
    "# 将得到的所有出租车上下车点的列表构建DataFrame并输出中间文件保存，路径为：data/processed/output_data/\n",
    "ODs_df = pd.DataFrame(filtered_ODs_list,\n",
    "                      columns=['TaxiID', '时间', '经度', '纬度', '速度', '方向角', '空车 / 重车', '上下车点'])\n",
    "\n",
    "# 为了缩短运行时间，为了节省内存，取前12000条数据进行处理\n",
    "sample_OD_df = ODs_df[:12000]\n",
    "\n",
    "# dropna()能够找到DataFrame类型数据的空值，将空值所在的行/列删除后，将新的DataFrame作为返回值返回\n",
    "# how：筛选方式：any，表示该行/列只要有一个以上的空值，就删除该行/列；all，表示该行/列全部都为空值，就删除该行/列\n",
    "# axis：检查的轴：0或index，表示按行删除；1或columns，表示按列删除\n",
    "lat_lon_df = sample_OD_df[['纬度', '经度']].dropna(axis=0, how='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-12T09:00:45.607842Z",
     "start_time": "2023-05-12T08:58:26.849670Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "聚类后热点类簇Label：\n",
      "0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, -1\n"
     ]
    }
   ],
   "source": [
    "distance_matrix = squareform(pdist(lat_lon_df, (lambda u, v: haversine(u, v))))\n",
    "\n",
    "# # DBSCAN调参\n",
    "# result_df, eps_best, min_samples_best = DBSCAN_adjustParameters(distance_matrix,'precomputed')\n",
    "# # 输出调参结果\n",
    "# print('选用的eps参数为：%f ，选用的min_samples参数为：%d \\n' % (eps_best,min_samples_best))\n",
    "# # DBSCAN聚类，使用上面经过调参得到的最优eps和min_samples\n",
    "\n",
    "# DBSCAN聚类，使用上面经过调参得到的最优eps和min_samples\n",
    "# od_label = DBSCAN().fit_predict(distance_matrix)\n",
    "od_label = DBSCAN(eps=190, min_samples=6, metric='precomputed').fit_predict(distance_matrix)\n",
    "od_label = od_label.tolist()  # 使用DBSCAN获得的热点聚类标签\n",
    "\n",
    "# 计算噪声点的数量，在使用Sklearn进行DBSCAN聚类时，“-1”标签表示未能划分到任何类簇中的噪声点\n",
    "noise = 0\n",
    "for l in od_label:\n",
    "    if l == -1:\n",
    "        noise += 1\n",
    "\n",
    "# 确定出租车OD热点类簇的类型\n",
    "label_str = [str(ol) for ol in list(set(od_label))]\n",
    "print('聚类后热点类簇Label：\\n' + ', '.join(label_str))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-12T09:01:05.716955Z",
     "start_time": "2023-05-12T09:00:45.608841Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\CliQue\\AppData\\Local\\Temp\\ipykernel_22732\\2785236518.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  sample_OD_df['热点类别'] = od_label\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "清洗噪声后OD点数：1886\n",
      "聚类号为 0 的热点聚类中的热点平均经纬度为: (114.249180,30.540472)\n",
      "聚类号为 0 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区马鹦路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江堤街道', 'adcode': '420105', 'town_code': '420105011', 'business': '江腾苑,五里墩,鹦鹉/鹦鹉大道', 'regionsName': '江腾广场-A座西北97米'}\n",
      "聚类号为 1 的热点聚类中的热点平均经纬度为: (114.277876,30.571374)\n",
      "聚类号为 1 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区大夹街6-112', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '满春街街道', 'adcode': '420103', 'town_code': '420103005', 'business': '汉正街,满春,江汉路', 'regionsName': '大夹街服装批发市场内,贵夫人(友谊南路店)附近21米'}\n",
      "聚类号为 2 的热点聚类中的热点平均经纬度为: (114.267898,30.571614)\n",
      "聚类号为 2 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区长堤街611号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '汉正街道', 'adcode': '420104', 'town_code': '420104009', 'business': '汉正街,利济路,武胜路', 'regionsName': '三曙社区西北136米'}\n",
      "聚类号为 3 的热点聚类中的热点平均经纬度为: (114.211907,30.556917)\n",
      "聚类号为 3 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区芳草路16号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '琴断口街道', 'adcode': '420105', 'town_code': '420105008', 'business': '墨水湖,琴断口,王家湾', 'regionsName': '汉阳区西192米'}\n",
      "聚类号为 4 的热点聚类中的热点平均经纬度为: (114.286384,30.578724)\n",
      "聚类号为 4 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区民生路花楼街198号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '花楼街街道', 'adcode': '420103', 'town_code': '420103002', 'business': '前进,江汉路,民权', 'regionsName': '宝利金国际广场内,好一家超市(花楼街店)附近38米'}\n",
      "聚类号为 5 的热点聚类中的热点平均经纬度为: (114.279052,30.608898)\n",
      "聚类号为 5 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区三眼桥路19', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '唐家墩街街道', 'adcode': '420103', 'town_code': '420103009', 'business': '香港路,建设大道,唐家墩', 'regionsName': '禧邦可广场内,汉口银行(总行营业部)北112米'}\n",
      "聚类号为 6 的热点聚类中的热点平均经纬度为: (114.328219,30.532502)\n",
      "聚类号为 6 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区丁字桥路23号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '武珞路,紫阳路,丁字桥', 'regionsName': '中南花园西南81米'}\n",
      "聚类号为 7 的热点聚类中的热点平均经纬度为: (114.251690,30.618445)\n",
      "聚类号为 7 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区汉口站横路', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '常青街街道', 'adcode': '420103', 'town_code': '420103012', 'business': '青年路,常青路,新华路', 'regionsName': '汉口站内,献血点(汉口火车站捐血屋)南177米'}\n",
      "聚类号为 8 的热点聚类中的热点平均经纬度为: (114.182719,30.568184)\n",
      "聚类号为 8 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区仙女山路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '永丰街道', 'adcode': '420105', 'town_code': '420105010', 'business': '琴台大道', 'regionsName': '泰和超市(汉阳大道店)西70米'}\n",
      "聚类号为 9 的热点聚类中的热点平均经纬度为: (114.251463,30.575136)\n",
      "聚类号为 9 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区京汉大道195号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '荣华街道', 'adcode': '420104', 'town_code': '420104006', 'business': '宝丰,崇仁路,硚口路', 'regionsName': '玉带家园东北90米'}\n",
      "聚类号为 10 的热点聚类中的热点平均经纬度为: (114.264446,30.551169)\n",
      "聚类号为 10 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区北城路16号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '建桥街道', 'adcode': '420105', 'town_code': '420105002', 'business': '钟家村,建桥,鹦鹉/鹦鹉大道', 'regionsName': '武汉市第五医院西94米'}\n",
      "聚类号为 11 的热点聚类中的热点平均经纬度为: (114.265377,30.585122)\n",
      "聚类号为 11 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区步礄桥', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '万松街街道', 'adcode': '420103', 'town_code': '420103008', 'business': '西北湖,万松/万松园,新华路', 'regionsName': '广播大院内,湖北人民广播电台北118米'}\n",
      "聚类号为 12 的热点聚类中的热点平均经纬度为: (114.287205,30.595770)\n",
      "聚类号为 12 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区解放南路129', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '球场街道', 'adcode': '420102', 'town_code': '420102008', 'business': '香港路,大智路,球场街', 'regionsName': '金茂大厦附近27米'}\n",
      "聚类号为 13 的热点聚类中的热点平均经纬度为: (114.310858,30.532206)\n",
      "聚类号为 13 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中山路人行通道', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '首义路街道', 'adcode': '420106', 'town_code': '420106010', 'business': '首义路,紫阳路,武珞路', 'regionsName': '武昌站内,战友平价超市东北51米'}\n",
      "聚类号为 14 的热点聚类中的热点平均经纬度为: (114.298177,30.522296)\n",
      "聚类号为 14 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区白沙洲大道404-14号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '白沙洲街道', 'adcode': '420106', 'town_code': '420106009', 'business': '武泰闸,白沙洲,紫阳路', 'regionsName': '万隆广场北87米'}\n",
      "聚类号为 15 的热点聚类中的热点平均经纬度为: (114.417456,30.608563)\n",
      "聚类号为 15 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区黄鹤路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '和平街道', 'adcode': '420111', 'town_code': '420111008', 'business': '', 'regionsName': '武汉站内,武汉火车站(地铁站)西南183米'}\n",
      "聚类号为 16 的热点聚类中的热点平均经纬度为: (114.420079,30.610634)\n",
      "聚类号为 16 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区武汉站东一路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '和平街道', 'adcode': '420111', 'town_code': '420111008', 'business': '厂前', 'regionsName': '武汉站内,湖北特产店附近18米'}\n",
      "聚类号为 17 的热点聚类中的热点平均经纬度为: (114.213567,30.773436)\n",
      "聚类号为 17 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市黄陂区廊桥3', 'province': '湖北省', 'city': '武汉市', 'district': '黄陂区', 'town': '天河街道', 'adcode': '420116', 'town_code': '420116007', 'business': '', 'regionsName': '武汉天河国际机场内,星巴克(天河机场T3安检内东店)西南86米'}\n",
      "聚类号为 18 的热点聚类中的热点平均经纬度为: (114.236011,30.630968)\n",
      "聚类号为 18 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区新湾二路9号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '汉兴街街道', 'adcode': '420103', 'town_code': '420103013', 'business': '汉兴,常青路', 'regionsName': '南航小区内'}\n",
      "聚类号为 19 的热点聚类中的热点平均经纬度为: (114.206408,30.592183)\n",
      "聚类号为 19 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区古田四路13号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '韩家墩街道', 'adcode': '420104', 'town_code': '420104002', 'business': '古田,韩家墩,汉西', 'regionsName': '联发九都府内,宜嘉超市(古田四路店)附近26米'}\n",
      "聚类号为 20 的热点聚类中的热点平均经纬度为: (114.349299,30.590717)\n",
      "聚类号为 20 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区团结大道1009-35号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '洪山街街道', 'adcode': '420111', 'town_code': '420111007', 'business': '杨园,徐东大街,徐东销品茂', 'regionsName': '新世纪花园内,风行晓晓副食附近22米'}\n",
      "聚类号为 21 的热点聚类中的热点平均经纬度为: (114.383689,30.607249)\n",
      "聚类号为 21 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区仁和路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '和平街道', 'adcode': '420111', 'town_code': '420111008', 'business': '', 'regionsName': '仁和路(地铁站)附近25米'}\n",
      "聚类号为 22 的热点聚类中的热点平均经纬度为: (114.264769,30.579797)\n",
      "聚类号为 22 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区京汉大道499号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '六角亭街道', 'adcode': '420104', 'town_code': '420104010', 'business': '武广,万松/万松园,武胜路', 'regionsName': '利济北路(地铁站)附近18米'}\n",
      "聚类号为 23 的热点聚类中的热点平均经纬度为: (114.331275,30.546513)\n",
      "聚类号为 23 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中南路106号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '洪山广场,水果湖,中北路', 'regionsName': '中国铁路武汉局集团有限公司西北113米'}\n",
      "聚类号为 24 的热点聚类中的热点平均经纬度为: (114.132379,30.621564)\n",
      "聚类号为 24 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区五环大道88', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '吴家山,长青', 'regionsName': '亿达华庭内,兴业银行(武汉临空港支行)附近19米'}\n",
      "聚类号为 25 的热点聚类中的热点平均经纬度为: (114.149223,30.621148)\n",
      "聚类号为 25 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区一清路10号', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '吴家山', 'regionsName': '额头湾小区内,紫燕百味鸡(一清路店)南116米'}\n",
      "聚类号为 26 的热点聚类中的热点平均经纬度为: (114.363226,30.587715)\n",
      "聚类号为 26 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区永乐路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '洪山街街道', 'adcode': '420111', 'town_code': '420111007', 'business': '徐东大街,杨园', 'regionsName': '长源东湖尚郡内,省电社区西149米'}\n",
      "聚类号为 27 的热点聚类中的热点平均经纬度为: (114.312881,30.541637)\n",
      "聚类号为 27 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中山路438号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '首义路街道', 'adcode': '420106', 'town_code': '420106010', 'business': '大东门,武珞路,首义路', 'regionsName': '武汉大学附属爱尔眼科医院西55米'}\n",
      "聚类号为 28 的热点聚类中的热点平均经纬度为: (114.322035,30.578563)\n",
      "聚类号为 28 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区友谊大道350号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '徐家棚街道', 'adcode': '420106', 'town_code': '420106003', 'business': '徐家棚,友谊大道,积玉桥', 'regionsName': '武汉航海职业技术学院南140米'}\n",
      "聚类号为 29 的热点聚类中的热点平均经纬度为: (114.403428,30.499286)\n",
      "聚类号为 29 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区雄楚大街988', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '关山,光谷创业街,鲁巷', 'regionsName': '武汉市关山中学内,雄楚大道1062号关山中学2号楼东52米'}\n",
      "聚类号为 30 的热点聚类中的热点平均经纬度为: (114.347014,30.508616)\n",
      "聚类号为 30 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区雄楚大道352号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '珞南,南湖,卓刀泉', 'regionsName': '鸿福花园内,洪福公园东南78米'}\n",
      "聚类号为 31 的热点聚类中的热点平均经纬度为: (114.267649,30.622062)\n",
      "聚类号为 31 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区发展大道307', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '唐家墩街街道', 'adcode': '420103', 'town_code': '420103009', 'business': '唐家墩,香港路,新华路', 'regionsName': '顶琇晶城内,民众口腔(发展大道店)附近33米'}\n",
      "聚类号为 32 的热点聚类中的热点平均经纬度为: (114.320602,30.536677)\n",
      "聚类号为 32 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区武珞路358-附10', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '中南路/中南,紫阳路,武珞路', 'regionsName': '省客集团傅家坡汽车客运站西南146米'}\n",
      "聚类号为 33 的热点聚类中的热点平均经纬度为: (114.240099,30.551147)\n",
      "聚类号为 33 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区墨水湖路53号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '五里墩街道', 'adcode': '420105', 'town_code': '420105007', 'business': '五里墩,墨水湖,琴台', 'regionsName': '武汉市汉阳医院内,武汉市公安局交通管理局醒酒中心东北54米'}\n",
      "聚类号为 34 的热点聚类中的热点平均经纬度为: (114.251882,30.580617)\n",
      "聚类号为 34 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区解放大道1089-附2', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '宝丰街道', 'adcode': '420104', 'town_code': '420104005', 'business': '宝丰,万松/万松园,崇仁路', 'regionsName': '梅园宾馆(解放大道店)内,梅园宾馆-西院内0米'}\n",
      "聚类号为 35 的热点聚类中的热点平均经纬度为: (114.247391,30.587632)\n",
      "聚类号为 35 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区建设大道365', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '宝丰街道', 'adcode': '420104', 'town_code': '420104005', 'business': '王家墩,宝丰,建设大道', 'regionsName': '武汉信息港南97米'}\n",
      "聚类号为 36 的热点聚类中的热点平均经纬度为: (114.294517,30.605963)\n",
      "聚类号为 36 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区解放公园路41-附7', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '劳动街道', 'adcode': '420102', 'town_code': '420102009', 'business': '解放公园,劳动,三阳路', 'regionsName': '武汉市育才高级中学东北115米'}\n",
      "聚类号为 37 的热点聚类中的热点平均经纬度为: (114.336042,30.590733)\n",
      "聚类号为 37 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区友谊大道46号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '徐家棚街道', 'adcode': '420106', 'town_code': '420106003', 'business': '徐东销品茂,徐家棚,徐东大街', 'regionsName': '中商世界里·鹏程销品茂购物中心西135米'}\n",
      "聚类号为 38 的热点聚类中的热点平均经纬度为: (114.264041,30.575586)\n",
      "聚类号为 38 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区荣华东街20-附7', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '六角亭街道', 'adcode': '420104', 'town_code': '420104010', 'business': '武胜路,武广,崇仁路', 'regionsName': '荣东社区内,白玉兰酒店(武汉武胜路地铁站店)附近18米'}\n",
      "聚类号为 39 的热点聚类中的热点平均经纬度为: (114.326213,30.582225)\n",
      "聚类号为 39 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区友谊大道368号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '徐家棚街道', 'adcode': '420106', 'town_code': '420106003', 'business': '徐家棚,友谊大道,徐东大街', 'regionsName': '三角花园内,三角大厦附近38米'}\n",
      "聚类号为 40 的热点聚类中的热点平均经纬度为: (114.338079,30.604126)\n",
      "聚类号为 40 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区杨园街124号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '杨园街道', 'adcode': '420106', 'town_code': '420106002', 'business': '杨园,余家头', 'regionsName': '中铁第四勘察设计院集团有限公司内,铁道第四勘察设计院通号处城轨所西南72米'}\n",
      "聚类号为 41 的热点聚类中的热点平均经纬度为: (114.393438,30.506752)\n",
      "聚类号为 41 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区民族大道12号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '卓刀泉街道', 'adcode': '420111', 'town_code': '420111006', 'business': '关山,光谷创业街,鲁巷', 'regionsName': '光谷世界城西126米'}\n",
      "聚类号为 42 的热点聚类中的热点平均经纬度为: (114.376330,30.498452)\n",
      "聚类号为 42 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区康福路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '卓刀泉,虎泉', 'regionsName': '南湖康泰花园内,百佳惠超市(康泰花园店)西南114米'}\n",
      "聚类号为 43 的热点聚类中的热点平均经纬度为: (114.280232,30.621066)\n",
      "聚类号为 43 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区黄孝河路69号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '花桥街道', 'adcode': '420102', 'town_code': '420102015', 'business': '花桥,竹叶山,建设大道', 'regionsName': '凯旋大厦内,武汉市退役军人事务局附近46米'}\n",
      "聚类号为 44 的热点聚类中的热点平均经纬度为: (114.259283,30.552247)\n",
      "聚类号为 44 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区汉阳大道150号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '建桥街道', 'adcode': '420105', 'town_code': '420105002', 'business': '鹦鹉/鹦鹉大道,琴台,翠微', 'regionsName': '闽东国际商业广场-2栋楼附近49米'}\n",
      "聚类号为 45 的热点聚类中的热点平均经纬度为: (114.242492,30.534353)\n",
      "聚类号为 45 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区三里坡路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江堤街道', 'adcode': '420105', 'town_code': '420105011', 'business': '江腾苑,鹦鹉/鹦鹉大道,洲头', 'regionsName': '汉阳区新城丽景内,新城丽景-A区西南162米'}\n",
      "聚类号为 46 的热点聚类中的热点平均经纬度为: (114.210161,30.585344)\n",
      "聚类号为 46 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区简易路4号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '韩家墩街道', 'adcode': '420104', 'town_code': '420104002', 'business': '汉西,韩家墩,古田', 'regionsName': '武汉市硚口区人民政府内,硚口区北196米'}\n",
      "聚类号为 47 的热点聚类中的热点平均经纬度为: (114.348391,30.555115)\n",
      "聚类号为 47 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区东湖路169号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '水果湖街道', 'adcode': '420106', 'town_code': '420106012', 'business': '水果湖,中北路,汉街', 'regionsName': '武汉大学(医学部)内,武汉大学中南医院内0米'}\n",
      "聚类号为 49 的热点聚类中的热点平均经纬度为: (114.255683,30.591547)\n",
      "聚类号为 49 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区航空小路19号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '万松街街道', 'adcode': '420103', 'town_code': '420103008', 'business': '王家墩,建设大道,万松/万松园', 'regionsName': '万松街电力社区十二中宿舍内'}\n",
      "聚类号为 50 的热点聚类中的热点平均经纬度为: (114.230719,30.587801)\n",
      "聚类号为 50 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区建设大道152号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '汉水桥街道', 'adcode': '420104', 'town_code': '420104004', 'business': '汉西,汉西路,宗关', 'regionsName': '湘商大厦东南226米'}\n",
      "聚类号为 51 的热点聚类中的热点平均经纬度为: (114.211415,30.588667)\n",
      "聚类号为 51 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区解放大道148-18号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '韩家墩街道', 'adcode': '420104', 'town_code': '420104002', 'business': '古田,汉西,韩家墩', 'regionsName': '汉正瑞鑫大酒店附近44米'}\n",
      "聚类号为 52 的热点聚类中的热点平均经纬度为: (114.278789,30.588176)\n",
      "聚类号为 52 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区江汉路商圈解放大道1411号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '新华街街道', 'adcode': '420103', 'town_code': '420103007', 'business': '新华路,江汉路,台北路', 'regionsName': '循礼门饭店内'}\n",
      "聚类号为 53 的热点聚类中的热点平均经纬度为: (114.288089,30.589034)\n",
      "聚类号为 53 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区吉庆街154-附1', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '大智街道', 'adcode': '420102', 'town_code': '420102002', 'business': '大智路,江汉路,南京路', 'regionsName': '合兴里小区内'}\n",
      "聚类号为 54 的热点聚类中的热点平均经纬度为: (114.336121,30.521798)\n",
      "聚类号为 54 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区石牌岭路239号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '石牌岭,珞南,武珞路', 'regionsName': '洪山菜薹公园东120米'}\n",
      "聚类号为 55 的热点聚类中的热点平均经纬度为: (114.199158,30.614978)\n",
      "聚类号为 55 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区丰泰路', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '长丰街道', 'adcode': '420104', 'town_code': '420104011', 'business': '古田', 'regionsName': '长丰城内'}\n",
      "聚类号为 56 的热点聚类中的热点平均经纬度为: (114.259292,30.556563)\n",
      "聚类号为 56 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区琴台路10号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '晴川街道', 'adcode': '420105', 'town_code': '420105004', 'business': '月湖,琴台,鹦鹉/鹦鹉大道', 'regionsName': '月湖风景区内,古琴台东南113米'}\n",
      "聚类号为 57 的热点聚类中的热点平均经纬度为: (114.294124,30.536798)\n",
      "聚类号为 57 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区紫阳路93号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '黄鹤楼街道', 'adcode': '420106', 'town_code': '420106007', 'business': '首义路,紫阳路,阅马场', 'regionsName': '武汉大学人民医院南135米'}\n",
      "聚类号为 58 的热点聚类中的热点平均经纬度为: (114.347371,30.528265)\n",
      "聚类号为 58 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区珞狮路112号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '珞南,街道口,武珞路', 'regionsName': '阜华大厦西104米'}\n",
      "聚类号为 59 的热点聚类中的热点平均经纬度为: (114.339907,30.595976)\n",
      "聚类号为 59 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区友谊大道555号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '徐家棚街道', 'adcode': '420106', 'town_code': '420106003', 'business': '徐东大街,杨园,徐东销品茂', 'regionsName': '徐东小区-57号楼内0米'}\n",
      "聚类号为 60 的热点聚类中的热点平均经纬度为: (114.223257,30.564690)\n",
      "聚类号为 60 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区罗七路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '琴断口街道', 'adcode': '420105', 'town_code': '420105008', 'business': '琴断口,五里墩,月湖', 'regionsName': '湖北中烟卷烟材料厂北129米'}\n",
      "聚类号为 61 的热点聚类中的热点平均经纬度为: (114.340941,30.561426)\n",
      "聚类号为 61 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中北路96号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '水果湖街道', 'adcode': '420106', 'town_code': '420106012', 'business': '中北路,水果湖,汉街', 'regionsName': '广泽中心内,交通银行(武汉水果湖支行)西南98米'}\n",
      "聚类号为 62 的热点聚类中的热点平均经纬度为: (114.270409,30.613877)\n",
      "聚类号为 62 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区三眼桥北路8', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '唐家墩街街道', 'adcode': '420103', 'town_code': '420103009', 'business': '香港路,唐家墩,新华路', 'regionsName': '新村社区西南95米'}\n",
      "聚类号为 63 的热点聚类中的热点平均经纬度为: (114.275610,30.578164)\n",
      "聚类号为 63 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区友谊路50号-10', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '民意街街道', 'adcode': '420103', 'town_code': '420103006', 'business': '友谊路,前进,江汉路', 'regionsName': '舞台天下内,中国银行(武汉友谊支行)附近20米'}\n",
      "聚类号为 64 的热点聚类中的热点平均经纬度为: (114.136509,30.648870)\n",
      "聚类号为 64 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区三店中路', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '三店', 'regionsName': '鑫海花城内,金星幼儿园附近18米'}\n",
      "聚类号为 65 的热点聚类中的热点平均经纬度为: (114.128748,30.630377)\n",
      "聚类号为 65 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区园丁街3号', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '吴家山,长青,三店', 'regionsName': '吴家山第一小学(东校区)内'}\n",
      "聚类号为 66 的热点聚类中的热点平均经纬度为: (114.177482,30.606970)\n",
      "聚类号为 66 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区工农路', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '易家街道', 'adcode': '420104', 'town_code': '420104012', 'business': '古田,易家墩', 'regionsName': '古田一路(地铁站)附近24米'}\n",
      "聚类号为 67 的热点聚类中的热点平均经纬度为: (114.283692,30.585957)\n",
      "聚类号为 67 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区吉庆街21号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '大智街道', 'adcode': '420102', 'town_code': '420102002', 'business': '大智路,江汉路,南京路', 'regionsName': '慈德里小区内,佳丽广场附近10米'}\n",
      "聚类号为 68 的热点聚类中的热点平均经纬度为: (114.275768,30.623315)\n",
      "聚类号为 68 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区俊才街40号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '花桥街道', 'adcode': '420102', 'town_code': '420102015', 'business': '竹叶山,花桥,唐家墩', 'regionsName': '武华住宅小区-四区南49米'}\n",
      "聚类号为 69 的热点聚类中的热点平均经纬度为: (114.282960,30.605193)\n",
      "聚类号为 69 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区香港路218-2号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '西马街道', 'adcode': '420102', 'town_code': '420102007', 'business': '香港路,球场街,劳动', 'regionsName': '武汉儿童医院内,武汉市妇女儿童医疗保健中心南111米'}\n",
      "聚类号为 70 的热点聚类中的热点平均经纬度为: (114.355444,30.569045)\n",
      "聚类号为 70 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区黄鹂路39号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '水果湖街道', 'adcode': '420106', 'town_code': '420106012', 'business': '水果湖,中北路,徐东大街', 'regionsName': '湖北省广播电视局内,交通银行(武汉东亭支行)附近48米'}\n",
      "聚类号为 71 的热点聚类中的热点平均经纬度为: (114.351170,30.595303)\n",
      "聚类号为 71 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区铁机西路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '和平街道', 'adcode': '420111', 'town_code': '420111008', 'business': '杨园,徐东大街,余家头', 'regionsName': '中南宿舍西南142米'}\n",
      "聚类号为 72 的热点聚类中的热点平均经纬度为: (114.397583,30.476232)\n",
      "聚类号为 72 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区软件园路1', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '关山', 'regionsName': '光谷软件园内,交通银行大楼内0米'}\n",
      "聚类号为 73 的热点聚类中的热点平均经纬度为: (114.402940,30.470286)\n",
      "聚类号为 73 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江夏区关山大道489号', 'province': '湖北省', 'city': '武汉市', 'district': '江夏区', 'town': '东湖开发区', 'adcode': '420115', 'town_code': '420115400', 'business': '关山', 'regionsName': '武汉市东湖高新技术开发区关山一路汽车电子产业园内,有家超市(茅店山东路店)东147米'}\n",
      "聚类号为 74 的热点聚类中的热点平均经纬度为: (114.376094,30.507393)\n",
      "聚类号为 74 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区虎泉街271-43号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '虎泉,卓刀泉', 'regionsName': '永利国际大厦内,武汉遇见影院民宿附近34米'}\n",
      "聚类号为 75 的热点聚类中的热点平均经纬度为: (114.299170,30.608807)\n",
      "聚类号为 75 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区解放大道1320号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '永清街道', 'adcode': '420102', 'town_code': '420102006', 'business': '解放公园,永清,黄浦路', 'regionsName': '仁义社区西北64米'}\n",
      "聚类号为 76 的热点聚类中的热点平均经纬度为: (114.349927,30.573438)\n",
      "聚类号为 76 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中北路265号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '水果湖街道', 'adcode': '420106', 'town_code': '420106012', 'business': '徐东大街,水果湖,中北路', 'regionsName': '世纪彩城内,世纪大厦(秦园东路)内0米'}\n",
      "聚类号为 77 的热点聚类中的热点平均经纬度为: (114.327046,30.538974)\n",
      "聚类号为 77 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中南路10-8号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '武珞路,中南路/中南,紫阳路', 'regionsName': '中商广场(中南路店)东94米'}\n",
      "聚类号为 78 的热点聚类中的热点平均经纬度为: (114.327629,30.661975)\n",
      "聚类号为 78 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区汉黄路', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '丹水池街道', 'adcode': '420102', 'town_code': '420102012', 'business': '后湖,丹水池,百步亭', 'regionsName': '美联公园前西南296米'}\n",
      "聚类号为 79 的热点聚类中的热点平均经纬度为: (114.215718,30.599027)\n",
      "聚类号为 79 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区汉西二路293号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '韩家墩街道', 'adcode': '420104', 'town_code': '420104002', 'business': '古田,汉西,宗关', 'regionsName': '汉西三路板材大市场附近36米'}\n",
      "聚类号为 80 的热点聚类中的热点平均经纬度为: (114.323315,30.642742)\n",
      "聚类号为 80 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区解放大道1966-6号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '丹水池街道', 'adcode': '420102', 'town_code': '420102012', 'business': '丹水池,百步亭,后湖', 'regionsName': '百步亭大厦东126米'}\n",
      "聚类号为 81 的热点聚类中的热点平均经纬度为: (114.266306,30.615753)\n",
      "聚类号为 81 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区新华下路183号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '唐家墩街街道', 'adcode': '420103', 'town_code': '420103009', 'business': '新华路,菱角湖,唐家墩', 'regionsName': '唐家墩小学东南95米'}\n",
      "聚类号为 82 的热点聚类中的热点平均经纬度为: (114.260356,30.612757)\n",
      "聚类号为 82 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区新华路481号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '常青街街道', 'adcode': '420103', 'town_code': '420103012', 'business': '唐家墩,常青路,菱角湖', 'regionsName': '新华西美林公馆东北115米'}\n",
      "聚类号为 83 的热点聚类中的热点平均经纬度为: (114.315319,30.658864)\n",
      "聚类号为 83 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区后湖大道', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '后湖街道', 'adcode': '420102', 'town_code': '420102017', 'business': '百步亭,后湖', 'regionsName': '武汉市汉铁高级中学西南167米'}\n",
      "聚类号为 84 的热点聚类中的热点平均经纬度为: (114.234645,30.521574)\n",
      "聚类号为 84 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区江堤中路108号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江堤街道', 'adcode': '420105', 'town_code': '420105011', 'business': '鹦鹉/鹦鹉大道,洲头', 'regionsName': '武汉市公安局汉阳区分局江堤派出所内'}\n",
      "聚类号为 85 的热点聚类中的热点平均经纬度为: (114.221914,30.586350)\n",
      "聚类号为 85 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区建设大道75号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '宗关街道', 'adcode': '420104', 'town_code': '420104003', 'business': '宗关,汉西,汉西路', 'regionsName': '电源小区东南100米'}\n",
      "聚类号为 86 的热点聚类中的热点平均经纬度为: (114.136133,30.626151)\n",
      "聚类号为 86 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区东吴大道917号', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '吴家山', 'regionsName': '西湖广场西北100米'}\n",
      "聚类号为 87 的热点聚类中的热点平均经纬度为: (114.214676,30.603940)\n",
      "聚类号为 87 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区汉西二路特8号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '长丰街道', 'adcode': '420104', 'town_code': '420104011', 'business': '古田,汉西,宗关', 'regionsName': '云鹤三村西77米'}\n",
      "聚类号为 88 的热点聚类中的热点平均经纬度为: (114.292898,30.581179)\n",
      "聚类号为 88 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区沿江大道136号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '一元街道', 'adcode': '420102', 'town_code': '420102003', 'business': '南京路,江汉路,民权', 'regionsName': '武汉港大楼内'}\n",
      "聚类号为 89 的热点聚类中的热点平均经纬度为: (114.280920,30.615106)\n",
      "聚类号为 89 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区黄孝河路60', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '花桥街道', 'adcode': '420102', 'town_code': '420102015', 'business': '解放公园,建设大道,花桥', 'regionsName': '颐和丽晶附近35米'}\n",
      "聚类号为 90 的热点聚类中的热点平均经纬度为: (114.258362,30.598574)\n",
      "聚类号为 90 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区青年路314号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '北湖街街道', 'adcode': '420103', 'town_code': '420103010', 'business': '王家墩,北湖,万松/万松园', 'regionsName': '花园道写字楼北60米'}\n",
      "聚类号为 91 的热点聚类中的热点平均经纬度为: (114.233516,30.627939)\n",
      "聚类号为 91 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区常青路163-2号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '汉兴街街道', 'adcode': '420103', 'town_code': '420103013', 'business': '汉兴,常青路', 'regionsName': '台银大厦北87米'}\n",
      "聚类号为 92 的热点聚类中的热点平均经纬度为: (114.363638,30.515855)\n",
      "聚类号为 92 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区虎泉街80-31号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '卓刀泉,虎泉,陈家湾', 'regionsName': '虎泉夜市美食广场西北63米'}\n",
      "聚类号为 93 的热点聚类中的热点平均经纬度为: (114.199522,30.569516)\n",
      "聚类号为 93 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区玫瑰街237', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江汉二桥街道', 'adcode': '420105', 'town_code': '420105009', 'business': '王家湾,江汉二桥,琴台大道', 'regionsName': '德才小区(玫瑰街)内,中国光大银行(玫瑰苑社区支行)附近20米'}\n",
      "聚类号为 94 的热点聚类中的热点平均经纬度为: (114.238144,30.653247)\n",
      "聚类号为 94 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区G347(金银潭大道)', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '金银湖街道', 'adcode': '420112', 'town_code': '420112015', 'business': '常青路', 'regionsName': '金银潭(地铁站)东北88米'}\n",
      "聚类号为 95 的热点聚类中的热点平均经纬度为: (114.174003,30.639764)\n",
      "聚类号为 95 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区环湖路辅路', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '金银湖街道', 'adcode': '420112', 'town_code': '420112015', 'business': '金银湖', 'regionsName': '调度通信大楼西南238米'}\n",
      "聚类号为 96 的热点聚类中的热点平均经纬度为: (114.325066,30.526680)\n",
      "聚类号为 96 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区丁字桥路51号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '中南路/中南,武珞路,丁字桥', 'regionsName': '中铁十一局集团建筑安装工程有限公司西82米'}\n",
      "聚类号为 97 的热点聚类中的热点平均经纬度为: (114.417586,30.502913)\n",
      "聚类号为 97 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区光谷大道16号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '光谷创业街,关山', 'regionsName': '丽顿酒店(光谷店)东52米'}\n",
      "聚类号为 98 的热点聚类中的热点平均经纬度为: (114.333886,30.551970)\n",
      "聚类号为 98 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中北路44-3号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '水果湖街道', 'adcode': '420106', 'town_code': '420106012', 'business': '水果湖,楚河汉街,中北路', 'regionsName': '长城汇东121米'}\n",
      "聚类号为 99 的热点聚类中的热点平均经纬度为: (114.271683,30.565815)\n",
      "聚类号为 99 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区五彩正巷22', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '汉正街道', 'adcode': '420104', 'town_code': '420104009', 'business': '汉正街,利济路,武胜路', 'regionsName': '汉正街龙腾第一大道内,汉正街第一大道蓝宝石座内0米'}\n",
      "聚类号为 100 的热点聚类中的热点平均经纬度为: (114.384779,30.501038)\n",
      "聚类号为 100 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区雄楚大道838号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '鲁巷,虎泉,卓刀泉', 'regionsName': '季佳·荟雄楚北113米'}\n",
      "聚类号为 101 的热点聚类中的热点平均经纬度为: (114.257998,30.592635)\n",
      "聚类号为 101 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区青年路200号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '万松街街道', 'adcode': '420103', 'town_code': '420103008', 'business': '青年路,建设大道,万松/万松园', 'regionsName': '武汉中海中心西南86米'}\n",
      "聚类号为 102 的热点聚类中的热点平均经纬度为: (114.301169,30.557575)\n",
      "聚类号为 102 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中山路178号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '粮道街道', 'adcode': '420106', 'town_code': '420106005', 'business': '粮道街,积玉桥,友谊大道', 'regionsName': '中国建设银行(武汉凤凰支行)西131米'}\n",
      "聚类号为 103 的热点聚类中的热点平均经纬度为: (114.347175,30.585728)\n",
      "聚类号为 103 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区徐东大街165号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '洪山街街道', 'adcode': '420111', 'town_code': '420111007', 'business': '杨园,徐东大街,徐东销品茂', 'regionsName': '福星惠誉国际城悦公馆西92米'}\n",
      "聚类号为 104 的热点聚类中的热点平均经纬度为: (114.339669,30.581065)\n",
      "聚类号为 104 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区秦园东路', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '积玉桥街道', 'adcode': '420106', 'town_code': '420106001', 'business': '徐东大街,友谊大道,徐家棚', 'regionsName': '水岸星城内,茗点咖啡(秦园东路店)西北145米'}\n",
      "聚类号为 105 的热点聚类中的热点平均经纬度为: (114.263589,30.596722)\n",
      "聚类号为 105 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区建设大道558号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '万松街街道', 'adcode': '420103', 'town_code': '420103008', 'business': '万松/万松园,北湖,建设大道', 'regionsName': '武汉新华voco酒店内,新华大饭店-商贸楼东南63米'}\n",
      "聚类号为 106 的热点聚类中的热点平均经纬度为: (114.308554,30.620487)\n",
      "聚类号为 106 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区解放大道1983号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '二七街道', 'adcode': '420102', 'town_code': '420102010', 'business': '黄浦路,二七,建设大道', 'regionsName': '头道街(地铁站)附近48米'}\n",
      "聚类号为 107 的热点聚类中的热点平均经纬度为: (114.158383,30.680621)\n",
      "聚类号为 107 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区十字西街20', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '径河街道', 'adcode': '420112', 'town_code': '420112007', 'business': '径河', 'regionsName': '武汉市东西湖区径河小学东北71米'}\n",
      "聚类号为 108 的热点聚类中的热点平均经纬度为: (114.201831,30.565729)\n",
      "聚类号为 108 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区汉阳大道695', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江汉二桥街道', 'adcode': '420105', 'town_code': '420105009', 'business': '王家湾,江汉二桥,琴台大道', 'regionsName': '武汉市公安局交通管理局直属大队北62米'}\n",
      "聚类号为 109 的热点聚类中的热点平均经纬度为: (114.392547,30.500096)\n",
      "聚类号为 109 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区雄楚大道851号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '卓刀泉街道', 'adcode': '420111', 'town_code': '420111006', 'business': '关山,鲁巷,光谷创业街', 'regionsName': '洪福添美城市广场西北140米'}\n",
      "聚类号为 110 的热点聚类中的热点平均经纬度为: (114.249735,30.605182)\n",
      "聚类号为 110 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区云彩路', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '江汉经济开发区', 'adcode': '420103', 'town_code': '420103400', 'business': '常青路,青年路,新华路', 'regionsName': '武汉范湖万达广场内,武汉汉口喜来登大酒店东北57米'}\n",
      "聚类号为 111 的热点聚类中的热点平均经纬度为: (114.207555,30.551928)\n",
      "聚类号为 111 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区十升二路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '琴断口街道', 'adcode': '420105', 'town_code': '420105008', 'business': '琴断口,墨水湖,王家湾', 'regionsName': '龙阳1号内,汉口银行(芳草路支行)附近7米'}\n",
      "聚类号为 112 的热点聚类中的热点平均经纬度为: (114.322600,30.521075)\n",
      "聚类号为 112 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区楚雄大街149号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '丁字桥,南湖,南湖花园', 'regionsName': '莲溪寺南村铁路小区东南164米'}\n",
      "聚类号为 113 的热点聚类中的热点平均经纬度为: (114.329184,30.554193)\n",
      "聚类号为 113 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区沙湖大道', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '洪山广场,水果湖,中北路', 'regionsName': '湖北省人才服务局内,湖北省人力资源社会保障厅社保综合大楼南64米'}\n",
      "聚类号为 114 的热点聚类中的热点平均经纬度为: (114.266105,30.599170)\n",
      "聚类号为 114 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区新华路305号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '北湖街街道', 'adcode': '420103', 'town_code': '420103010', 'business': '新华路,北湖,建设大道', 'regionsName': '建银大厦东71米'}\n",
      "聚类号为 115 的热点聚类中的热点平均经纬度为: (114.379888,30.504129)\n",
      "聚类号为 115 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区雄楚大道704号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '卓刀泉街道', 'adcode': '420111', 'town_code': '420111006', 'business': '虎泉,卓刀泉,鲁巷', 'regionsName': '丽橙酒店趣(武汉光谷杨家湾地铁站店)西南81米'}\n",
      "聚类号为 116 的热点聚类中的热点平均经纬度为: (114.210493,30.511893)\n",
      "聚类号为 116 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区梅林六街', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江堤街道', 'adcode': '420105', 'town_code': '420105011', 'business': '', 'regionsName': '广电兰亭时代内,菜猫生鲜附近44米'}\n",
      "聚类号为 117 的热点聚类中的热点平均经纬度为: (114.401573,30.509700)\n",
      "聚类号为 117 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区珞瑜路151号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '关山,光谷创业街,鲁巷', 'regionsName': '湖北省中医院(光谷院区)西北178米'}\n",
      "聚类号为 118 的热点聚类中的热点平均经纬度为: (114.136324,30.619865)\n",
      "聚类号为 118 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区东西湖大道6197号', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '长青街道', 'adcode': '420112', 'town_code': '420112008', 'business': '吴家山', 'regionsName': '佳柏现代城西北83米'}\n",
      "聚类号为 119 的热点聚类中的热点平均经纬度为: (114.312973,30.628844)\n",
      "聚类号为 119 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区二七路60', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '百步亭花园', 'adcode': '420102', 'town_code': '420102400', 'business': '二七,黄浦路', 'regionsName': '江岸铁路文化宫(桃园小路)内'}\n",
      "聚类号为 120 的热点聚类中的热点平均经纬度为: (114.238903,30.578099)\n",
      "聚类号为 120 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区解放大道741号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '汉水桥街道', 'adcode': '420104', 'town_code': '420104004', 'business': '宝丰,汉水桥,硚口路', 'regionsName': '硚房翰林珑城东南100米'}\n",
      "聚类号为 122 的热点聚类中的热点平均经纬度为: (114.266045,30.547091)\n",
      "聚类号为 122 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区拦江路144号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '建桥街道', 'adcode': '420105', 'town_code': '420105002', 'business': '钟家村,鹦鹉/鹦鹉大道,建桥', 'regionsName': '武汉市晴川高级中学南60米'}\n",
      "聚类号为 123 的热点聚类中的热点平均经纬度为: (114.276109,30.554535)\n",
      "聚类号为 123 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区莲花湖路10号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '建桥街道', 'adcode': '420105', 'town_code': '420105002', 'business': '建桥,钟家村,琴台', 'regionsName': '武汉铁路局工务大修段西南209米'}\n",
      "聚类号为 124 的热点聚类中的热点平均经纬度为: (114.352383,30.512626)\n",
      "聚类号为 124 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区雄楚大道307号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '珞南,南湖,陈家湾', 'regionsName': '万科主场东南63米'}\n",
      "聚类号为 125 的热点聚类中的热点平均经纬度为: (114.308389,30.500712)\n",
      "聚类号为 125 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区南李路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '狮子山街道', 'adcode': '420111', 'town_code': '420111003', 'business': '南湖,南湖花园,红旗', 'regionsName': '南国花郡内'}\n",
      "聚类号为 126 的热点聚类中的热点平均经纬度为: (114.381718,30.615825)\n",
      "聚类号为 126 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区仁和路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '和平街道', 'adcode': '420111', 'town_code': '420111008', 'business': '建设二路,钢花村,冶金', 'regionsName': '武钢文化体育园北118米'}\n",
      "聚类号为 127 的热点聚类中的热点平均经纬度为: (114.249481,30.713580)\n",
      "聚类号为 127 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市黄陂区巨龙大道201-附1', 'province': '湖北省', 'city': '武汉市', 'district': '黄陂区', 'town': '盘龙城经济开发区', 'adcode': '420116', 'town_code': '420116403', 'business': '', 'regionsName': '武汉天河机场东希尔顿欢朋酒店南63米'}\n",
      "聚类号为 128 的热点聚类中的热点平均经纬度为: (114.164710,30.507696)\n",
      "聚类号为 128 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市蔡甸区G318(东风大道高架)', 'province': '湖北省', 'city': '武汉市', 'district': '蔡甸区', 'town': '沌口街道', 'adcode': '420114', 'town_code': '420114070', 'business': '经开万达,江汉大学', 'regionsName': '体育中心(地铁站)西南124米'}\n",
      "聚类号为 129 的热点聚类中的热点平均经纬度为: (114.251784,30.631887)\n",
      "聚类号为 129 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区常青五路160号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '汉兴街街道', 'adcode': '420103', 'town_code': '420103013', 'business': '新华路,常青路,汉兴', 'regionsName': '常二社区内,火锅物语食材超市(常青五路店)附近3米'}\n",
      "聚类号为 130 的热点聚类中的热点平均经纬度为: (114.239464,30.528511)\n",
      "聚类号为 130 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区向阳东路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江堤街道', 'adcode': '420105', 'town_code': '420105011', 'business': '鹦鹉/鹦鹉大道,洲头', 'regionsName': '汉博佳园内,威威副食经营部(江堤中路店)东84米'}\n",
      "聚类号为 131 的热点聚类中的热点平均经纬度为: (114.130940,30.634473)\n",
      "聚类号为 131 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区五环大道328号', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '吴家山,三店', 'regionsName': '全名健身中心东南148米'}\n",
      "聚类号为 132 的热点聚类中的热点平均经纬度为: (114.358727,30.582866)\n",
      "聚类号为 132 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区中北东路16号-附1', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '洪山街街道', 'adcode': '420111', 'town_code': '420111007', 'business': '徐东大街,杨园', 'regionsName': '正堂山外山内,正堂时代内0米'}\n",
      "聚类号为 133 的热点聚类中的热点平均经纬度为: (114.252667,30.636546)\n",
      "聚类号为 133 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区姑嫂树路1号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '汉兴街街道', 'adcode': '420103', 'town_code': '420103013', 'business': '汉兴,常青路,新华路', 'regionsName': '花·易派花园内,江汉区姑嫂树菜市场附近21米'}\n",
      "聚类号为 134 的热点聚类中的热点平均经纬度为: (114.207462,30.568353)\n",
      "聚类号为 134 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区玫瑰街87号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江汉二桥街道', 'adcode': '420105', 'town_code': '420105009', 'business': '王家湾,江汉二桥,琴台大道', 'regionsName': '汉江世纪星城内,全季酒店(王家湾店)东南83米'}\n",
      "聚类号为 135 的热点聚类中的热点平均经纬度为: (114.214704,30.526812)\n",
      "聚类号为 135 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区梅林西路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '江堤街道', 'adcode': '420105', 'town_code': '420105011', 'business': '', 'regionsName': '博大星光国际东103米'}\n",
      "聚类号为 136 的热点聚类中的热点平均经纬度为: (114.364841,30.508031)\n",
      "聚类号为 136 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区雄楚大道466号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '卓刀泉,虎泉,陈家湾', 'regionsName': '名都花园内,交通银行(武汉卓刀泉支行)附近9米'}\n",
      "聚类号为 137 的热点聚类中的热点平均经纬度为: (114.237419,30.608282)\n",
      "聚类号为 137 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区振兴路25号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '常青街街道', 'adcode': '420103', 'town_code': '420103012', 'business': '常青路,汉西', 'regionsName': '复兴一村内,江汉区振兴路小学东南125米'}\n",
      "聚类号为 138 的热点聚类中的热点平均经纬度为: (114.267199,30.639594)\n",
      "聚类号为 138 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区秋桂街', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '后湖街道', 'adcode': '420102', 'town_code': '420102017', 'business': '', 'regionsName': '鹏记 汉口花园内,汉口花园-四期内0米'}\n",
      "聚类号为 139 的热点聚类中的热点平均经纬度为: (114.221459,30.558806)\n",
      "聚类号为 139 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区麒麟路38号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '琴断口街道', 'adcode': '420105', 'town_code': '420105008', 'business': '琴断口,墨水湖,五里墩', 'regionsName': '汉阳区琴断口街麒麟社区内,琴断口街麒麟社区-东区附近32米'}\n",
      "聚类号为 140 的热点聚类中的热点平均经纬度为: (114.257241,30.543299)\n",
      "聚类号为 140 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区拦江路248号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '建桥街道', 'adcode': '420105', 'town_code': '420105002', 'business': '腰路堤,鹦鹉/鹦鹉大道,翠微', 'regionsName': '翠微福苑北163米'}\n",
      "聚类号为 141 的热点聚类中的热点平均经纬度为: (114.259566,30.534969)\n",
      "聚类号为 141 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区鹦鹉大道398-2号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '鹦鹉街道', 'adcode': '420105', 'town_code': '420105005', 'business': '鹦鹉/鹦鹉大道,江汉大学,江腾苑', 'regionsName': '联合一百(贤贤超市)西南66米'}\n",
      "聚类号为 142 的热点聚类中的热点平均经纬度为: (114.335163,30.556257)\n",
      "聚类号为 142 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中北路103-50号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '水果湖街道', 'adcode': '420106', 'town_code': '420106012', 'business': '水果湖,楚河汉街,中北路', 'regionsName': '凯德1818东北133米'}\n",
      "聚类号为 143 的热点聚类中的热点平均经纬度为: (114.368808,30.520522)\n",
      "聚类号为 143 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区珞瑜路425', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '卓刀泉,虎泉,珞南', 'regionsName': '清和广场附近32米'}\n",
      "聚类号为 144 的热点聚类中的热点平均经纬度为: (114.219340,30.550732)\n",
      "聚类号为 144 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区麒麟路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '五里墩街道', 'adcode': '420105', 'town_code': '420105007', 'business': '墨水湖,琴断口,五里墩', 'regionsName': '七里新村内,惠民副食店西南54米'}\n",
      "聚类号为 145 的热点聚类中的热点平均经纬度为: (114.228071,30.558782)\n",
      "聚类号为 145 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区汉阳大道574号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '五里墩街道', 'adcode': '420105', 'town_code': '420105007', 'business': '五里墩,墨水湖,琴台', 'regionsName': '汉阳区疾病预防控制中心南50米'}\n",
      "聚类号为 146 的热点聚类中的热点平均经纬度为: (114.213822,30.562663)\n",
      "聚类号为 146 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区汉阳大道660', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '琴断口街道', 'adcode': '420105', 'town_code': '420105008', 'business': '琴断口,墨水湖,王家湾', 'regionsName': '纽宾凯公园里内'}\n",
      "聚类号为 147 的热点聚类中的热点平均经纬度为: (114.195564,30.597660)\n",
      "聚类号为 147 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区解放大道97号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '古田街道', 'adcode': '420104', 'town_code': '420104001', 'business': '古田,古田路,易家墩', 'regionsName': '中百仓储(古田路店)东135米'}\n",
      "聚类号为 148 的热点聚类中的热点平均经纬度为: (114.291624,30.657780)\n",
      "聚类号为 148 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区和谐大道', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '后湖街道', 'adcode': '420102', 'town_code': '420102017', 'business': '后湖', 'regionsName': '吉祥谷内,武汉和谐中西结合医院附近14米'}\n",
      "聚类号为 149 的热点聚类中的热点平均经纬度为: (114.371569,30.519974)\n",
      "聚类号为 149 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区珞喻路481号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '卓刀泉,虎泉,珞南', 'regionsName': '全季酒店(武汉光谷珞喻路店)附近29米'}\n",
      "聚类号为 150 的热点聚类中的热点平均经纬度为: (114.285825,30.587549)\n",
      "聚类号为 150 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区吉庆街100号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '大智街道', 'adcode': '420102', 'town_code': '420102002', 'business': '大智路,江汉路,南京路', 'regionsName': '福忠里内'}\n",
      "聚类号为 151 的热点聚类中的热点平均经纬度为: (114.241634,30.547797)\n",
      "聚类号为 151 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区马沧湖路246号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '五里墩街道', 'adcode': '420105', 'town_code': '420105007', 'business': '五里墩,墨水湖,月湖', 'regionsName': '武汉市交通科技学校西北71米'}\n",
      "聚类号为 152 的热点聚类中的热点平均经纬度为: (114.198003,30.595993)\n",
      "聚类号为 152 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区解放大道70', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '古田街道', 'adcode': '420104', 'town_code': '420104001', 'business': '古田,古田路,易家墩', 'regionsName': '古田三路融侨锦城内,康泰健口腔门诊附近24米'}\n",
      "聚类号为 153 的热点聚类中的热点平均经纬度为: (114.216098,30.586593)\n",
      "聚类号为 153 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区解放大道363号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '韩家墩街道', 'adcode': '420104', 'town_code': '420104002', 'business': '宗关,汉西,韩家墩', 'regionsName': '汉口1872北101米'}\n",
      "聚类号为 154 的热点聚类中的热点平均经纬度为: (114.250683,30.572011)\n",
      "聚类号为 154 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区中山大道39号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '汉中街道', 'adcode': '420104', 'town_code': '420104008', 'business': '崇仁路,汉中,硚口路', 'regionsName': '硚口公园西南140米'}\n",
      "聚类号为 155 的热点聚类中的热点平均经纬度为: (114.349391,30.533363)\n",
      "聚类号为 155 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区珞珈山路13号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '珞南,街道口,武珞路', 'regionsName': '学府鑫苑西北65米'}\n",
      "聚类号为 156 的热点聚类中的热点平均经纬度为: (114.207953,30.517347)\n",
      "聚类号为 156 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区梅林西路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '四新街道', 'adcode': '420105', 'town_code': '420105012', 'business': '', 'regionsName': '绿地中央广场-C区南59米'}\n",
      "聚类号为 157 的热点聚类中的热点平均经纬度为: (114.269242,30.592705)\n",
      "聚类号为 157 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区新华路218号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '新华街街道', 'adcode': '420103', 'town_code': '420103007', 'business': '新华路,万松/万松园,西北湖', 'regionsName': '浦发银行大厦内,上海浦东发展银行(武汉分行)附近37米'}\n",
      "聚类号为 158 的热点聚类中的热点平均经纬度为: (114.406836,30.503580)\n",
      "聚类号为 158 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区关山路27号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '关山,光谷创业街,鲁巷', 'regionsName': '光谷时代广场西146米'}\n",
      "聚类号为 159 的热点聚类中的热点平均经纬度为: (114.306071,30.656715)\n",
      "聚类号为 159 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区温馨路', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '后湖街道', 'adcode': '420102', 'town_code': '420102017', 'business': '百步亭,后湖', 'regionsName': '统百中心南191米'}\n",
      "聚类号为 160 的热点聚类中的热点平均经纬度为: (114.335232,30.510404)\n",
      "聚类号为 160 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区雄楚大道266号-8号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '南湖,南湖花园,珞南', 'regionsName': '三鸿家园内,烟酒商贸附近46米'}\n",
      "聚类号为 161 的热点聚类中的热点平均经纬度为: (114.144318,30.632936)\n",
      "聚类号为 161 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区二雅路307', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '吴家山,三店', 'regionsName': '海景花园内,中国农业发展银行(武汉市东西湖区支行)附近29米'}\n",
      "聚类号为 162 的热点聚类中的热点平均经纬度为: (114.319937,30.584820)\n",
      "聚类号为 162 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区和平大道563号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '徐家棚街道', 'adcode': '420106', 'town_code': '420106003', 'business': '徐家棚,友谊大道', 'regionsName': '绿地国际金融城内,绿地蓝海-A座附近48米'}\n",
      "聚类号为 163 的热点聚类中的热点平均经纬度为: (114.261459,30.631308)\n",
      "聚类号为 163 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区绿柳路', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '汉兴街街道', 'adcode': '420103', 'town_code': '420103013', 'business': '汉兴,新华路,常青路', 'regionsName': '如家酒店(石桥地铁站店)附近25米'}\n",
      "聚类号为 164 的热点聚类中的热点平均经纬度为: (114.358931,30.500379)\n",
      "聚类号为 164 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区南湖北路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '卓刀泉,珞南,陈家湾', 'regionsName': '南湖半岛东北118米'}\n",
      "聚类号为 165 的热点聚类中的热点平均经纬度为: (114.337282,30.532227)\n",
      "聚类号为 165 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区武珞路613号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '武珞路,中南路/中南,石牌岭', 'regionsName': '武商亚贸广场购物中心北88米'}\n",
      "聚类号为 166 的热点聚类中的热点平均经纬度为: (114.354633,30.526730)\n",
      "聚类号为 166 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区珞瑜路100号', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '珞南,街道口,陈家湾', 'regionsName': '武汉大学继续教育学院西南85米'}\n",
      "聚类号为 167 的热点聚类中的热点平均经纬度为: (114.314403,30.647214)\n",
      "聚类号为 167 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区百步亭花园路33号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '百步亭花园', 'adcode': '420102', 'town_code': '420102400', 'business': '百步亭,后湖,丹水池', 'regionsName': '百步亭房地产代理有限公司内,交通银行(武汉百步亭支行)附近10米'}\n",
      "聚类号为 168 的热点聚类中的热点平均经纬度为: (114.279946,30.637884)\n",
      "聚类号为 168 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区德胜堂路', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '后湖街道', 'adcode': '420102', 'town_code': '420102017', 'business': '后湖', 'regionsName': '金岛金桥壹号西北165米'}\n",
      "聚类号为 169 的热点聚类中的热点平均经纬度为: (114.306296,30.487729)\n",
      "聚类号为 169 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区北苑一路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '狮子山街道', 'adcode': '420111', 'town_code': '420111003', 'business': '南湖,南湖花园,红旗', 'regionsName': '湖北工业大学内,李家墩一村-3号楼附近43米'}\n",
      "聚类号为 170 的热点聚类中的热点平均经纬度为: (114.330397,30.517758)\n",
      "聚类号为 170 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区雄楚大道228号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中南路街道', 'adcode': '420106', 'town_code': '420106011', 'business': '南湖,南湖花园,石牌岭', 'regionsName': '武汉乐都汇时尚购物广场(石牌岭路店)南120米'}\n",
      "聚类号为 171 的热点聚类中的热点平均经纬度为: (114.326342,30.492049)\n",
      "聚类号为 171 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区新城家园路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '狮子山街道', 'adcode': '420111', 'town_code': '420111003', 'business': '南湖花园,南湖', 'regionsName': '鸿城家园内,SBI创意大厦南61米'}\n",
      "聚类号为 172 的热点聚类中的热点平均经纬度为: (114.276243,30.632283)\n",
      "聚类号为 172 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区石桥二路9', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '后湖街道', 'adcode': '420102', 'town_code': '420102017', 'business': '后湖,竹叶山,花桥', 'regionsName': '征原电气西北179米'}\n",
      "聚类号为 173 的热点聚类中的热点平均经纬度为: (114.267779,30.541490)\n",
      "聚类号为 173 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区阳新路', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '鹦鹉街道', 'adcode': '420105', 'town_code': '420105005', 'business': '鹦鹉/鹦鹉大道,腰路堤,江汉大学', 'regionsName': '世茂锦绣长江52内,武汉世茂希尔顿酒店(武汉世茂店)西83米'}\n",
      "聚类号为 174 的热点聚类中的热点平均经纬度为: (114.358568,30.524852)\n",
      "聚类号为 174 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区珞瑜路236', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '珞南街道', 'adcode': '420111', 'town_code': '420111001', 'business': '卓刀泉,珞南,陈家湾', 'regionsName': '武汉电脑城南97米'}\n",
      "聚类号为 175 的热点聚类中的热点平均经纬度为: (114.446462,30.503324)\n",
      "聚类号为 175 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区秦云路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '关山街道', 'adcode': '420111', 'town_code': '420111002', 'business': '光谷创业街', 'regionsName': '蓝光COCO时代东北194米'}\n",
      "聚类号为 176 的热点聚类中的热点平均经纬度为: (114.245370,30.553970)\n",
      "聚类号为 176 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区汉阳大道372号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '五里墩街道', 'adcode': '420105', 'town_code': '420105007', 'business': '五里墩,琴台,月湖', 'regionsName': '五琴里社区内,五里新村东南204米'}\n",
      "聚类号为 177 的热点聚类中的热点平均经纬度为: (114.296355,30.618885)\n",
      "聚类号为 177 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区黄浦大街83-4号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '劳动街道', 'adcode': '420102', 'town_code': '420102009', 'business': '永清,黄浦路,二七', 'regionsName': '黄浦景观大厦东南175米'}\n",
      "聚类号为 178 的热点聚类中的热点平均经纬度为: (114.231771,30.558192)\n",
      "聚类号为 178 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区汉阳大道510', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '五里墩街道', 'adcode': '420105', 'town_code': '420105007', 'business': '五里墩,墨水湖,琴台', 'regionsName': '宜尚酒店(武汉汉阳大道五里墩地铁站店)内,乾能大厦附近8米'}\n",
      "聚类号为 179 的热点聚类中的热点平均经纬度为: (114.291937,30.588607)\n",
      "聚类号为 179 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区胜利街90号', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '一元街道', 'adcode': '420102', 'town_code': '420102003', 'business': '大智路,车站,南京路', 'regionsName': '新丽大厦内,艾美迪精品酒店(汉口江滩店)附近18米'}\n",
      "聚类号为 180 的热点聚类中的热点平均经纬度为: (114.235782,30.556380)\n",
      "聚类号为 180 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市汉阳区汉阳大道446号', 'province': '湖北省', 'city': '武汉市', 'district': '汉阳区', 'town': '五里墩街道', 'adcode': '420105', 'town_code': '420105007', 'business': '五里墩,墨水湖,琴台', 'regionsName': '恒韵府附近37米'}\n",
      "聚类号为 181 的热点聚类中的热点平均经纬度为: (114.304073,30.526187)\n",
      "聚类号为 181 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中山路582号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '紫阳街道', 'adcode': '420106', 'town_code': '420106008', 'business': '紫阳路,白沙洲,武泰闸', 'regionsName': '梅家山综合楼附近40米'}\n",
      "聚类号为 182 的热点聚类中的热点平均经纬度为: (114.351157,30.536236)\n",
      "聚类号为 182 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区天鹅路', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '珞珈山街道', 'adcode': '420106', 'town_code': '420106013', 'business': '街道口,珞南,水果湖', 'regionsName': '武汉大学(文理学部)内,武汉大学本科生院楼西133米'}\n",
      "聚类号为 183 的热点聚类中的热点平均经纬度为: (114.220644,30.583060)\n",
      "聚类号为 183 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区解放大道234号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '宗关街道', 'adcode': '420104', 'town_code': '420104003', 'business': '宗关,汉西,韩家墩', 'regionsName': '宗关(地铁站)西北61米'}\n",
      "聚类号为 184 的热点聚类中的热点平均经纬度为: (114.389835,30.621642)\n",
      "聚类号为 184 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市青山区友谊大道905-3号', 'province': '湖北省', 'city': '武汉市', 'district': '青山区', 'town': '钢花村街道', 'adcode': '420107', 'town_code': '420107010', 'business': '钢花村,冶金,南干渠', 'regionsName': '梅竹园小区北164米'}\n",
      "聚类号为 185 的热点聚类中的热点平均经纬度为: (114.239633,30.629098)\n",
      "聚类号为 185 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区常青五路9号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '汉兴街街道', 'adcode': '420103', 'town_code': '420103013', 'business': '汉兴,常青路', 'regionsName': '武汉一初慧泉中学(金雅校区)内'}\n",
      "聚类号为 186 的热点聚类中的热点平均经纬度为: (114.234321,30.609712)\n",
      "聚类号为 186 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区发展大道45号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '常青街街道', 'adcode': '420103', 'town_code': '420103012', 'business': '常青路,汉西,古田', 'regionsName': '武汉市第三市政工程有限公司东北78米'}\n",
      "聚类号为 187 的热点聚类中的热点平均经纬度为: (114.195072,30.608248)\n",
      "聚类号为 187 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区古田二路119号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '长丰街道', 'adcode': '420104', 'town_code': '420104011', 'business': '古田,易家墩', 'regionsName': '天宇万象国际-2期内'}\n",
      "聚类号为 188 的热点聚类中的热点平均经纬度为: (114.291209,30.660582)\n",
      "聚类号为 188 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江岸区金桥大道', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '后湖街道', 'adcode': '420102', 'town_code': '420102017', 'business': '后湖', 'regionsName': '长江传媒大厦东北203米'}\n",
      "聚类号为 189 的热点聚类中的热点平均经纬度为: (114.269289,30.577744)\n",
      "聚类号为 189 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市硚口区游艺路103号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '六角亭街道', 'adcode': '420104', 'town_code': '420104010', 'business': '民意,武胜路,汉正街', 'regionsName': '游艺西村东94米'}\n",
      "聚类号为 191 的热点聚类中的热点平均经纬度为: (114.292780,30.552149)\n",
      "聚类号为 191 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中华路47号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '中华路街道', 'adcode': '420106', 'town_code': '420106006', 'business': '司门口,粮道街,阅马场', 'regionsName': '中国农业银行研发中心(武汉)东65米'}\n",
      "聚类号为 192 的热点聚类中的热点平均经纬度为: (114.256908,30.595448)\n",
      "聚类号为 192 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市江汉区建设大道508号', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '万松街街道', 'adcode': '420103', 'town_code': '420103008', 'business': '王家墩,建设大道,万松/万松园', 'regionsName': '武汉市兴盛大厦内,中国平安保险公司(青年路店)附近21米'}\n",
      "聚类号为 193 的热点聚类中的热点平均经纬度为: (114.367320,30.585319)\n",
      "聚类号为 193 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市洪山区华电小路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '洪山街街道', 'adcode': '420111', 'town_code': '420111007', 'business': '徐东大街,杨园', 'regionsName': '东湖景园内,何禾附近39米'}\n",
      "聚类号为 194 的热点聚类中的热点平均经纬度为: (114.138102,30.629217)\n",
      "聚类号为 194 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区三秀路378号', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '吴家山,三店', 'regionsName': '东顺擎天西南86米'}\n",
      "聚类号为 195 的热点聚类中的热点平均经纬度为: (114.111361,30.627627)\n",
      "聚类号为 195 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市东西湖区东吴大道', 'province': '湖北省', 'city': '武汉市', 'district': '东西湖区', 'town': '吴家山街道', 'adcode': '420112', 'town_code': '420112001', 'business': '', 'regionsName': '百洋商储购物广场(鑫城宜居店)附近31米'}\n",
      "聚类号为 197 的热点聚类中的热点平均经纬度为: (114.303545,30.557486)\n",
      "聚类号为 197 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区和平大道18号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '粮道街道', 'adcode': '420106', 'town_code': '420106005', 'business': '积玉桥,粮道街,友谊大道', 'regionsName': '中国建设银行(武汉凤凰支行)东154米'}\n",
      "聚类号为 198 的热点聚类中的热点平均经纬度为: (114.312069,30.553408)\n",
      "聚类号为 198 的热点聚类中的热点的平均地理位置逆向解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中山路360号', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '粮道街道', 'adcode': '420106', 'town_code': '420106005', 'business': '友谊大道,粮道街,小东门', 'regionsName': '泛悦中心(泛悦汇广场店)东南120米'}\n"
     ]
    },
    {
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",
      "text/plain": [
       "<Figure size 2000x1000 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 增加“热点类别”字段，并将聚类结果添加到“热点类别”字段中\n",
    "sample_OD_df['热点类别'] = od_label\n",
    "# 过滤存在噪声点的OD点对\n",
    "filtered_df = drop_noise(sample_OD_df)\n",
    "# 重新设置索引\n",
    "filtered_df.reset_index(drop=True, inplace=True)\n",
    "print('清洗噪声后OD点数：' + str(len(filtered_df)))\n",
    "\n",
    "plt.rcParams['font.family'] = ['SimHei']\n",
    "# 分割字图并设置整个图幅的大小为2000*1000\n",
    "fig, axes = plt.subplots(1, 2, figsize=(20, 10))\n",
    "\n",
    "# 上下车点的热点聚类结果显示，设置为子图1\n",
    "mpl.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "cluster_gdf = gpd.GeoDataFrame(filtered_df, geometry=gpd.points_from_xy(filtered_df['经度'], filtered_df['纬度']))\n",
    "ax1 = cluster_gdf.plot(ax=axes[0], column='热点类别', cmap='jet', legend=True, markersize=1, figsize=(10, 10))\n",
    "wuhan_road = gpd.GeoDataFrame.from_file('../data/road/WuhanPartroad/WHroad.shp')\n",
    "wuhan_road.plot(ax=ax1, linewidth=0.5, alpha=0.5, color='grey')\n",
    "ax1.set_title(\"2018年11月 上下车点的热点聚类结果显示\")\n",
    "\n",
    "# 输出按聚类结果划分的各个聚类的平均经纬度以及此点的地理位置逆向解析结果\n",
    "average_lon_cluster = [0] * (len(set(sample_OD_df['热点类别'])) - 1)\n",
    "average_lat_cluster = [0] * (len(set(sample_OD_df['热点类别'])) - 1)\n",
    "cluster_count = [0] * (len(set(sample_OD_df['热点类别'])) - 1)\n",
    "for index, row in filtered_df.iterrows():\n",
    "    # 对每个聚类（热点列表）的热点经纬度进行求和\n",
    "    v = row['热点类别']\n",
    "    average_lon_cluster[v] += row['经度']\n",
    "    average_lat_cluster[v] += row['纬度']\n",
    "    cluster_count[v] += 1\n",
    "for i in range(len(average_lon_cluster)):\n",
    "    # 取平均并输出结果信息\n",
    "    if cluster_count[i] == 0:\n",
    "        continue\n",
    "    average_lon_cluster_temp = average_lon_cluster[i] / cluster_count[i]\n",
    "    average_lat_cluster_temp = average_lat_cluster[i] / cluster_count[i]\n",
    "    print(\n",
    "        '聚类号为 %d 的热点聚类中的热点平均经纬度为: (%f,%f)' % (i, average_lon_cluster_temp, average_lat_cluster_temp))\n",
    "    print('聚类号为 %d 的热点聚类中的热点的平均地理位置逆向解析结果为：' % i)\n",
    "    print(coordinatesToPosition(average_lon_cluster_temp, average_lat_cluster_temp))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-05-12T09:05:39.747345Z",
     "start_time": "2023-05-12T09:05:07.008211Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "社区划分的个数：12\n",
      "\n",
      "各个社区的所属：\n",
      "[6, 13, 14, 15, 16, 20, 21, 23, 26, 27, 28, 29, 30, 32, 37, 39, 40, 41, 42, 47, 54, 58, 59, 61, 72, 73, 74, 76, 77, 92, 96, 97, 98, 100, 102, 103, 104, 108, 109, 111, 112, 113, 115, 117, 124, 125, 126, 132, 136, 137, 142, 143, 149, 155, 158, 160, 169, 170, 171, 175, 182, 184, 191, 193]\n",
      "[1, 2, 4, 5, 7, 8, 9, 11, 12, 31, 34, 35, 36, 49, 50, 51, 52, 55, 60, 63, 66, 68, 69, 78, 79, 80, 81, 89, 99, 101, 110, 114, 119, 120, 122, 127, 130, 145, 148, 150, 153, 154, 157, 159, 163, 165, 168, 179, 180, 183, 188, 189]\n",
      "[17, 18, 24, 25, 56, 62, 64, 65, 83, 85, 86, 87, 91, 94, 95, 106, 107, 118, 129, 131, 133, 151, 161, 162, 174, 177, 194]\n",
      "[0, 19, 43, 53, 67, 70, 71, 75, 82, 90, 138, 147, 167, 172, 173, 176, 186]\n",
      "[3, 33, 45, 46, 88, 93, 116, 123, 128, 139, 140, 144, 166, 178]\n",
      "[10, 38, 44, 57, 105, 134, 146, 152, 187, 192]\n",
      "[22, 84, 135, 141, 156, 181]\n",
      "[164]\n",
      "[185]\n",
      "[195]\n",
      "[197]\n",
      "[198]\n",
      "\n",
      "\n",
      "第 2 号节点为高强度节点，节点中各个热点的平均经纬度为：(114.267898,30.571614)\n",
      "此节点的在实际中的逆向地址解析结果为：\n",
      "{'address': '湖北省武汉市硚口区长堤街611号', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '汉正街道', 'adcode': '420104', 'town_code': '420104009', 'business': '汉正街,利济路,武胜路', 'regionsName': '三曙社区西北136米'}\n",
      "第 7 号节点为高强度节点，节点中各个热点的平均经纬度为：(114.251690,30.618445)\n",
      "此节点的在实际中的逆向地址解析结果为：\n",
      "{'address': '湖北省武汉市江汉区汉口站横路', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '常青街街道', 'adcode': '420103', 'town_code': '420103012', 'business': '青年路,常青路,新华路', 'regionsName': '汉口站内,献血点(汉口火车站捐血屋)南177米'}\n",
      "第 11 号节点为高强度节点，节点中各个热点的平均经纬度为：(114.265377,30.585122)\n",
      "此节点的在实际中的逆向地址解析结果为：\n",
      "{'address': '湖北省武汉市江汉区步礄桥', 'province': '湖北省', 'city': '武汉市', 'district': '江汉区', 'town': '万松街街道', 'adcode': '420103', 'town_code': '420103008', 'business': '西北湖,万松/万松园,新华路', 'regionsName': '广播大院内,湖北人民广播电台北118米'}\n",
      "第 13 号节点为高强度节点，节点中各个热点的平均经纬度为：(114.310858,30.532206)\n",
      "此节点的在实际中的逆向地址解析结果为：\n",
      "{'address': '湖北省武汉市武昌区中山路人行通道', 'province': '湖北省', 'city': '武汉市', 'district': '武昌区', 'town': '首义路街道', 'adcode': '420106', 'town_code': '420106010', 'business': '首义路,紫阳路,武珞路', 'regionsName': '武昌站内,战友平价超市东北51米'}\n",
      "第 15 号节点为高强度节点，节点中各个热点的平均经纬度为：(114.417456,30.608563)\n",
      "此节点的在实际中的逆向地址解析结果为：\n",
      "{'address': '湖北省武汉市洪山区黄鹤路', 'province': '湖北省', 'city': '武汉市', 'district': '洪山区', 'town': '和平街道', 'adcode': '420111', 'town_code': '420111008', 'business': '', 'regionsName': '武汉站内,武汉火车站(地铁站)西南183米'}\n",
      "第 15 号节点为高强度节点，节点中各个热点的平均经纬度为：(114.417456,30.608563)\n",
      "此节点的在实际中的逆向地址解析结果为：\n",
      "None\n",
      "第 34 号节点为高强度节点，节点中各个热点的平均经纬度为：(114.251882,30.580617)\n",
      "此节点的在实际中的逆向地址解析结果为：\n",
      "{'address': '湖北省武汉市硚口区解放大道1089-附2', 'province': '湖北省', 'city': '武汉市', 'district': '硚口区', 'town': '宝丰街道', 'adcode': '420104', 'town_code': '420104005', 'business': '宝丰,万松/万松园,崇仁路', 'regionsName': '梅园宾馆(解放大道店)内,梅园宾馆-西院内0米'}\n",
      "第 52 号节点为高强度节点，节点中各个热点的平均经纬度为：(114.288089,30.589034)\n",
      "此节点的在实际中的逆向地址解析结果为：\n",
      "{'address': '湖北省武汉市江岸区吉庆街154-附1', 'province': '湖北省', 'city': '武汉市', 'district': '江岸区', 'town': '大智街道', 'adcode': '420102', 'town_code': '420102002', 'business': '大智路,江汉路,南京路', 'regionsName': '合兴里小区内'}\n",
      "\n",
      "高强度节点中的所有OD点的空间分布情况为：\n",
      "{'江汉区 (Jianghan)': 308, '江夏区 (Jiangxia)': 0, '硚口区 (Qiaokou)': 144, \"江岸区 (Jiang'an)\": 33, '黄陂区 (Huangpi)': 0, '新洲区 (Xinzhou)': 0, '洪山区 (Hongshan)': 110, '武昌区 (Wuchang)': 58, '汉阳区 (Hanyang)': 0, '蔡甸区': 0, '汉南区 (Hannan)': 0, '东西湖区 (Dongxihu)': 0, '青山区 (Qingshan)': 0}\n",
      "按照空间分布密集程度进行排序的结果为：\n",
      "[('江汉区 (Jianghan)', 308), ('硚口区 (Qiaokou)', 144), ('洪山区 (Hongshan)', 110), ('武昌区 (Wuchang)', 58), (\"江岸区 (Jiang'an)\", 33), ('黄陂区 (Huangpi)', 0), ('青山区 (Qingshan)', 0), ('蔡甸区', 0), ('江夏区 (Jiangxia)', 0), ('汉阳区 (Hanyang)', 0), ('汉南区 (Hannan)', 0), ('新洲区 (Xinzhou)', 0), ('东西湖区 (Dongxihu)', 0)]\n",
      "\n",
      "所有节点中的所有OD点的空间分布情况为：\n",
      "{'江汉区 (Jianghan)': 482, '江夏区 (Jiangxia)': 0, '硚口区 (Qiaokou)': 273, \"江岸区 (Jiang'an)\": 231, '黄陂区 (Huangpi)': 52, '新洲区 (Xinzhou)': 0, '洪山区 (Hongshan)': 340, '武昌区 (Wuchang)': 259, '汉阳区 (Hanyang)': 139, '蔡甸区': 3, '汉南区 (Hannan)': 0, '东西湖区 (Dongxihu)': 107, '青山区 (Qingshan)': 0}\n",
      "按照空间分布密集程度进行排序的结果为：\n",
      "[('江汉区 (Jianghan)', 482), ('洪山区 (Hongshan)', 340), ('硚口区 (Qiaokou)', 273), ('武昌区 (Wuchang)', 259), (\"江岸区 (Jiang'an)\", 231), ('汉阳区 (Hanyang)', 139), ('东西湖区 (Dongxihu)', 107), ('黄陂区 (Huangpi)', 52), ('蔡甸区', 3), ('青山区 (Qingshan)', 0), ('江夏区 (Jiangxia)', 0), ('汉南区 (Hannan)', 0), ('新洲区 (Xinzhou)', 0)]\n",
      "\n",
      "\n",
      "介数中心性与度中心性拟合的三次曲线参数为：\n",
      "       3         2\n",
      "23.03 x - 12.18 x + 2.553 x + 0.01593\n",
      "介数中心性与接近中心性拟合的三次曲线参数为：\n",
      "       3         2\n",
      "85.19 x - 42.43 x + 5.168 x + 0.3255\n",
      "度中心性与接近中心性拟合的三次曲线参数为：\n",
      "       3         2\n",
      "44.88 x - 27.86 x + 4.794 x + 0.2478\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 3600x2700 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3200x2400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x1000 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 获取节点\n",
    "nodes = get_nodes(filtered_df)\n",
    "# 获取边\n",
    "edges = get_edges(filtered_df)\n",
    "# 开始构建空网络\n",
    "G = nx.Graph()\n",
    "# 分别填入节点和边到网络中\n",
    "G.add_nodes_from(nodes)\n",
    "G.add_weighted_edges_from(edges)\n",
    "# 对网络进行拓扑可视化展示\n",
    "# paint_network(G, nodes)\n",
    "\n",
    "# 获取社区的划分结果\n",
    "OD_Community1,node_community = gn_community_detect(G)\n",
    "print('社区划分的个数：' + str(len(OD_Community1)) + '\\n\\n各个社区的所属：')\n",
    "# 遍历社区集中的每一个社区，逐个输出每个社区所包括的热点类别\n",
    "for c in OD_Community1:\n",
    "    print(c)\n",
    "\n",
    "# 使用迭代器遍历清洗噪声后OD点数据集\n",
    "for index, row in filtered_df.iterrows():\n",
    "    v = row['热点类别']\n",
    "    # 根据热点类别得到这个OD点所属的热点社区，并将热点社区号作为新字段添加进去\n",
    "    filtered_df.loc[index,'热点社区'] = node_community[v]\n",
    "\n",
    "# 热点社区的空间分布，设置为子图2，和子图1一起绘制显示并保存图片在路径data/processed/output_picture/下\n",
    "community_gdf = gpd.GeoDataFrame(filtered_df, geometry=gpd.points_from_xy(filtered_df['经度'], filtered_df['纬度']))\n",
    "ax2 = community_gdf.plot(ax=axes[1],column='热点社区',cmap='hsv',legend=True,markersize=1,figsize=(10,10))  # 必要的绘图设置\n",
    "wuhan_road = gpd.GeoDataFrame.from_file('../data/road/WuhanPartroad/WHroad.shp')  # 叠加武汉市路网\n",
    "wuhan_road.plot(ax=ax2, linewidth=0.5, alpha=0.5, color='grey')\n",
    "ax2.set_title(\"2018年11月 热点社区的空间分布\")\n",
    "plt.suptitle('2018年11月 上下车点的热点聚类和热点社区的空间分布')\n",
    "\n",
    "plt.clf()\n",
    "# 对网络进行拓扑可视化展示\n",
    "paint_network(G, nodes)\n",
    "\n",
    "# 表示节点重要性的点权，即度（Strength）\n",
    "# g.degree()能够获得DegreeView对象\n",
    "# 对于无向图，顶点的度是指跟顶点相连的边的数量；\n",
    "# 对于有向图，顶点的图分为入度和出度，朝向顶点的边称作入度；背向顶点的边称作出度\n",
    "strength = dict(G.degree(weight='weight'))\n",
    "\n",
    "# 让matplotlib支持中文字体的显示\n",
    "mpl.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "# 设置绘图的分辨率，默认绘制的图形不够清晰\n",
    "plt.figure(figsize=(36,27))\n",
    "# 设置x轴为各个节点的列表\n",
    "# 注意除去0号节点（城市中心区域OD点稠密，形成范围较大的热点区域）\n",
    "X = [i for i in range(0,len(strength))][1:]\n",
    "# 设置y轴（绘制的数据）为空间交互网络各个节点的强度\n",
    "Y = [strength[key] for key in strength][1:]\n",
    "# 绘图\n",
    "fig = plt.figure()\n",
    "\n",
    "plt.bar(X,Y,1,color=\"steelblue\")\n",
    "plt.xlabel(\"节点ID\",fontsize=13)\n",
    "plt.ylabel(\"节点交互强度\",fontsize=13)\n",
    "# plt.grid(True)\n",
    "plt.title(\"出租车空间交互网络节点强度\",fontsize=13)\n",
    "\n",
    "# 基于出租车交互网络节点强度进行探索\n",
    "# 设置高强度节点的强度阈值为30\n",
    "strength_threshold = 30\n",
    "# 高强度节点的节点号列表\n",
    "high_strength = []\n",
    "# 高强度节点中的所有OD点\n",
    "high_strength_points_df = pd.DataFrame()\n",
    "\n",
    "for i in set(list(strength.keys())):\n",
    "    # 将节点强度超过阈值的节点视为高强度节点，获取节点号\n",
    "    if strength[i] >= strength_threshold:\n",
    "        high_strength.append(list(strength.keys())[list(strength.values()).index(strength[i])])\n",
    "print('\\n')\n",
    "\n",
    "for i in range(len(high_strength)):\n",
    "    # 节点的经纬度\n",
    "    AverLon = nodes[high_strength[i]][1]['AverLon']\n",
    "    AverLat = nodes[high_strength[i]][1]['AverLat']\n",
    "    print('第 %d 号节点为高强度节点，节点中各个热点的平均经纬度为：(%f,%f)' % (high_strength[i],AverLon,AverLat))\n",
    "    print('此节点的在实际中的逆向地址解析结果为：')\n",
    "    print(coordinatesToPosition(AverLon,AverLat))\n",
    "    high_strength_points_df = high_strength_points_df._append(filtered_df[filtered_df['热点类别'] == high_strength[i]])\n",
    "\n",
    "# 获取高强度节点中的所有OD点的GeoDataFrame以及所有OD点（包括非高强度节点中的OD点）的GeoDataFrame\n",
    "# 为了防止出错，重置两个使用的dataframe的索引\n",
    "high_strength_points_df = high_strength_points_df.reset_index(drop=True)\n",
    "filtered_df = filtered_df.reset_index(drop=True)\n",
    "high_strength_points_gdf = gpd.GeoDataFrame(high_strength_points_df, geometry=gpd.points_from_xy(high_strength_points_df['经度'], high_strength_points_df['纬度']),crs=4326)\n",
    "all_points_gdf = gpd.GeoDataFrame(filtered_df, geometry=gpd.points_from_xy(filtered_df['经度'], filtered_df['纬度']),crs=4326)\n",
    "# 读入武汉行政区划数据\n",
    "wuhan_region = gpd.GeoDataFrame.from_file('../data/武汉行政区划数据/武汉行政区划矢量图.shp')\n",
    "# OD点GeoDataFrame和行政区划数据的坐标系转成 WGS84大地坐标系(4326):\n",
    "wuhan_region = wuhan_region.to_crs(4326)\n",
    "\n",
    "# 新建一个保存每个行政区划内的OD点数目的字典\n",
    "ODs_in_wuhan_region_Count_high_strength = {}\n",
    "ODs_in_wuhan_region_Count_all = {}\n",
    "\n",
    "for i in range(len(wuhan_region)):\n",
    "    region_geo = wuhan_region.geometry[i]\n",
    "    name = wuhan_region.locname[i]\n",
    "    count_temp_high_strength = 0\n",
    "    count_temp_all = 0\n",
    "\n",
    "    # 统计高强度节点中的所有OD点的空间分布情况\n",
    "    for j in range(len(high_strength_points_gdf)):\n",
    "        point_geo = high_strength_points_gdf.geometry[j]\n",
    "        if point_geo.intersects(region_geo):\n",
    "            count_temp_high_strength += 1\n",
    "\n",
    "    # 统计所有节点（高强度、非高强度）中的所有OD点的空间分布情况\n",
    "    for j in range(len(all_points_gdf)):\n",
    "        point_geo = all_points_gdf.geometry[j]\n",
    "        if point_geo.intersects(region_geo):\n",
    "            count_temp_all += 1\n",
    "\n",
    "    # 将统计结果按武汉行政区划保存到字典中\n",
    "    ODs_in_wuhan_region_Count_high_strength[name] = count_temp_high_strength\n",
    "    ODs_in_wuhan_region_Count_all[name] = count_temp_all\n",
    "\n",
    "# 输出节点OD点的空间分布统计结果\n",
    "print('\\n高强度节点中的所有OD点的空间分布情况为：')\n",
    "print(ODs_in_wuhan_region_Count_high_strength)\n",
    "print('按照空间分布密集程度进行排序的结果为：')\n",
    "print(sorted(ODs_in_wuhan_region_Count_high_strength.items(), key=lambda kv:(kv[1], kv[0]),reverse=True))\n",
    "\n",
    "print('\\n所有节点中的所有OD点的空间分布情况为：')\n",
    "print(ODs_in_wuhan_region_Count_all)\n",
    "print('按照空间分布密集程度进行排序的结果为：')\n",
    "print(sorted(ODs_in_wuhan_region_Count_all.items(), key=lambda kv:(kv[1], kv[0]),reverse=True))\n",
    "print('\\n')\n",
    "\n",
    "# 将OD点数据合并到武汉市行政区划数据中\n",
    "ODCount_df = pd.DataFrame.from_dict(ODs_in_wuhan_region_Count_high_strength, orient='index', columns=['ODCount_High'])\n",
    "ODCount_df = ODCount_df._append(pd.DataFrame.from_dict(ODs_in_wuhan_region_Count_all, orient='index', columns=['ODCount_All']))\n",
    "ODCount_df = ODCount_df.reset_index().rename(columns={'index': 'locname'})\n",
    "ODCount_gdf = gpd.GeoDataFrame(ODCount_df)\n",
    "wuhan_region_withdata = wuhan_region.merge(ODCount_gdf, on='locname', how='left')\n",
    "\n",
    "# 绘图显示\n",
    "plt.rcParams['font.family'] = ['SimHei']\n",
    "# 分割字图并设置整个图幅的大小为2000*1000\n",
    "fig, axes = plt.subplots(1,2,figsize=(20,10))\n",
    "# k为显示的颜色数量\n",
    "ax1 = wuhan_region_withdata.plot(ax=axes[0],column='ODCount_High', k=8, cmap='Reds', legend=True)\n",
    "ax1.set_title(\"高强度节点中的所有OD点的空间分布情况\")\n",
    "ax2 = wuhan_region_withdata.plot(ax=axes[1],column='ODCount_All', k=8, cmap='Reds', legend=True)\n",
    "ax2.set_title(\"所有节点中的所有OD点的空间分布情况\")\n",
    "plt.suptitle('2018年11月 OD点的空间分布情况')\n",
    "# 基于出租车交互网络节点强度进行探索到这里结束\n",
    "\n",
    "# 基于出租车交互网络的节点中心性进行探索\n",
    "# 节点介数中心系数，中介中心性指的是一个结点担任其它两个结点之间最短路的桥梁的次数。一个结点充当“中介”的次数越高，它的中介中心度就越大\n",
    "node_betweenness_centrality = nx.betweenness_centrality(G)\n",
    "# 节点的度中心性是它所连接的节点的分数，一个节点的节点度越大就意味着这个节点的度中心性越高，该节点在网络中就越重要\n",
    "node_degree_centrality = nx.degree_centrality(G)\n",
    "# 节点的接近中心性，一个点的近性中心度较高，说明该点到网络中其他各点的距离总体来说较近，反之则较远\n",
    "node_closeness_centrality = nx.closeness_centrality(G, u=None, distance=None, wf_improved=True)\n",
    "\n",
    "# 将三个中心性测度值合并成dataframe\n",
    "centrality_list = [node_betweenness_centrality,node_degree_centrality,node_closeness_centrality]\n",
    "centrality_df = pd.DataFrame(centrality_list)\n",
    "# 重置索引名并转置\n",
    "centrality_df.index = ['node_betweenness_centrality','node_degree_centrality','node_closeness_centrality']\n",
    "centrality_df = centrality_df.transpose()\n",
    "# 如果需要对根据两个指标进行排序的话，可以参考以下语句，下面会用到\n",
    "# centrality_df.sort_values([\"node_betweenness_centrality\", \"node_degree_centrality\"], inplace=True, ascending=True)\n",
    "\n",
    "# 设置x轴,注意除去0号节点（城市中心区域OD点稠密，形成范围较大的热点区域）\n",
    "X = [i for i in range(0,len(node_betweenness_centrality))][1:]\n",
    "# 设置y轴（绘制的数据）为空间交互网络各个节点的三种中心性测度\n",
    "y1 = [node_betweenness_centrality[key] for key in node_betweenness_centrality][1:]\n",
    "y2 = [node_degree_centrality[key] for key in node_degree_centrality][1:]\n",
    "y3 = [node_closeness_centrality[key] for key in node_closeness_centrality][1:]\n",
    "\n",
    "plt.figure(figsize=(32,24))\n",
    "# 设置x轴刻度标签位置\n",
    "x = np.arange(len(X))\n",
    "# 每个柱子的宽度\n",
    "width = 0.25\n",
    "# 计算每个柱子在x轴上的位置，保证x轴刻度标签居中\n",
    "# x - width，x， x + width即每组数据在x轴上的位置\n",
    "plt.bar(x - width, y1, width, label='betweenness_centrality')\n",
    "plt.bar(x, y2, width, label='degree_centrality')\n",
    "plt.bar(x + width, y3, width, label='closeness_centrality')\n",
    "plt.ylabel('centrality', fontsize=36)\n",
    "plt.xlabel('节点序号', fontsize=36)\n",
    "plt.title('节点的三种度中心性测度柱状图显示结果', fontsize=48, pad=20)\n",
    "# x轴刻度标签位置不进行计算\n",
    "plt.xticks(x, labels=X)\n",
    "plt.legend()\n",
    "\n",
    "# 柱状图看得不直观，这里使用散点图加拟合三次曲线进行分析，三个测度两两之间成一幅图\n",
    "# 准备拟合的三次曲线的数据\n",
    "# 介数中心性与度中心性，获取二者之间散点数据拟合的三次曲线的参数，并得到三次曲线\n",
    "centrality_df.sort_values([\"node_betweenness_centrality\", \"node_degree_centrality\"], inplace=True, ascending=True)\n",
    "x_betweenness_degree = np.array(list(centrality_df['node_betweenness_centrality']))\n",
    "y_betweenness_degree = np.array(list(centrality_df['node_degree_centrality']))\n",
    "parameter_betweenness_degree = np.polyfit(x_betweenness_degree, y_betweenness_degree, deg=3)\n",
    "betweenness_degree_line3 = parameter_betweenness_degree[0] * x_betweenness_degree ** 3 + parameter_betweenness_degree[1] * x_betweenness_degree ** 2 + parameter_betweenness_degree[2] * x_betweenness_degree + parameter_betweenness_degree[3]\n",
    "\n",
    "# 介数中心性与接近中心性，获取二者之间散点数据拟合的三次曲线的参数\n",
    "centrality_df.sort_values([\"node_betweenness_centrality\", \"node_closeness_centrality\"], inplace=True, ascending=True)\n",
    "x_betweenness_closeness = np.array(list(centrality_df['node_betweenness_centrality']))\n",
    "y_betweenness_closeness = np.array(list(centrality_df['node_closeness_centrality']))\n",
    "parameter_betweenness_closeness = np.polyfit(x_betweenness_closeness, y_betweenness_closeness, deg=3)\n",
    "betweenness_closeness_line3 = parameter_betweenness_closeness[0] * x_betweenness_closeness ** 3 + parameter_betweenness_closeness[1] * x_betweenness_closeness ** 2 + parameter_betweenness_closeness[2] * x_betweenness_closeness + parameter_betweenness_closeness[3]\n",
    "\n",
    "# 度中心性与接近中心性，获取二者之间散点数据拟合的三次曲线的参数\n",
    "centrality_df.sort_values([\"node_degree_centrality\", \"node_closeness_centrality\"], inplace=True, ascending=True)\n",
    "x_degree_closeness = np.array(list(centrality_df['node_degree_centrality']))\n",
    "y_degree_closeness = np.array(list(centrality_df['node_closeness_centrality']))\n",
    "parameter_degree_closeness = np.polyfit(x_degree_closeness, y_degree_closeness, deg=3)\n",
    "degree_closeness_line3 = parameter_degree_closeness[0] * x_degree_closeness ** 3 + parameter_degree_closeness[1] * x_degree_closeness ** 2 + parameter_degree_closeness[2] * x_degree_closeness + parameter_degree_closeness[3]\n",
    "\n",
    "# 分割成3个子图并设置整个图幅的大小为3000*1000\n",
    "fig, ax = plt.subplots(1,3,figsize=(30,10))\n",
    "# 第一幅子图：介数中心性与度中心性之间的相关性\n",
    "ax[0].scatter(x_betweenness_degree, y_betweenness_degree)\n",
    "ax[0].plot(x_betweenness_degree, betweenness_degree_line3, color='g')\n",
    "ax[0].set_title(\"介数中心性与度中心性之间的相关性\")\n",
    "print('介数中心性与度中心性拟合的三次曲线参数为：')\n",
    "p1 = np.poly1d(parameter_betweenness_degree, variable='x')\n",
    "print(p1)\n",
    "\n",
    "# 第二幅子图：介数中心性与接近中心性之间的相关性\n",
    "ax[1].scatter(x_betweenness_closeness, y_betweenness_closeness)\n",
    "ax[1].plot(x_betweenness_closeness,betweenness_closeness_line3, color='g')\n",
    "ax[1].set_title(\"介数中心性与接近中心性之间的相关性\")\n",
    "print('介数中心性与接近中心性拟合的三次曲线参数为：')\n",
    "p2 = np.poly1d(parameter_betweenness_closeness, variable='x')\n",
    "print(p2)\n",
    "\n",
    "# 第三幅子图：度中心性与接近中心性之间的相关性\n",
    "ax[2].scatter(x_degree_closeness, y_degree_closeness)\n",
    "ax[2].plot(x_degree_closeness,degree_closeness_line3, color='g')\n",
    "ax[2].set_title(\"度中心性与接近中心性之间的相关性\")\n",
    "print('度中心性与接近中心性拟合的三次曲线参数为：')\n",
    "p3 = np.poly1d(parameter_degree_closeness, variable='x')\n",
    "print(p3)"
   ]
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